Climate change impacts and water temperature · best water temperature record in each region, including calculation of the rate of river water temperature change. 6. Seasonal analysis

Climate change impacts and watertemperature

Science Report: SC060017/SR

SCHO0707BNAG-E-E

Science Report Climate change impacts and water temperature i

The Environment Agency is the leading public body protecting andimproving the environment in England and Wales.

It’s our job to make sure that air, land and water are looked afterby everyone in today’s society, so that tomorrow’s generationsinherit a cleaner, healthier world.

Our work includes tackling flooding and pollution incidents,reducing industry’s impacts on the environment, cleaning up rivers,coastal waters and contaminated land, and improving wildlifehabitats.

This report is the result of research commissioned and funded bythe Environment Agency’s Science Programme.

Authors:D. Hammond and A.R. Pryce

Dissemination Status:Publicly available

Keywords:ANOVA, archive maintenance, climate change, moving average,river typology, river water temperature, statistical analysis,thermal regime

Research Contractor:D. Hammond and A.R. Pryce, Entec UK Ltd, 17 Angel Gate,City Road, London EC1V 2SH. Tel: 020 7843 1400

Environment Agency's Project Manager:Rob Evans, Cardiff

Science Project Number:SC060017

Product Code:SCHO0707BNAG-E-E

Published by:Environment Agency, Rio House, Waterside Drive,Aztec West, Almondsbury, Bristol, BS32 4UDTel: 01454 624400 Fax: 01454 624409www.environment-agency.gov.uk

ISBN: 978-1-84432-802-4

© Environment Agency – July 2007

All rights reserved. This document may be reproducedwith prior permission of the Environment Agency.

The views and statements expressed in this report arethose of the author alone. The views or statementsexpressed in this publication do not necessarilyrepresent the views of the Environment Agency and theEnvironment Agency cannot accept any responsibility forsuch views or statements.

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Further copies of this report are available from:The Environment Agency’s National Customer ContactCentre by emailing:[email protected] by telephoning 08708 506506.

http://www.environment-agency.gov.uk/

mailto:[email protected]

Science Report Climate change impacts and water temperatureii

Science at theEnvironment AgencyScience underpins the work of the Environment Agency. It provides an up-to-date understandingof the world about us and helps us to develop monitoring tools and techniques to manage ourenvironment as efficiently and effectively as possible.

The work of the Environment Agency’s Science Group is a key ingredient in the partnershipbetween research, policy and operations that enables the Environment Agency to protect andrestore our environment.

The science programme focuses on five main areas of activity:

• Setting the agenda, by identifying where strategic science can inform our evidence-based policies, advisory and regulatory roles;

• Funding science, by supporting programmes, projects and people in response tolong-term strategic needs, medium-term policy priorities and shorter-term operationalrequirements;

• Managing science, by ensuring that our programmes and projects are fit for purposeand executed according to international scientific standards;

• Carrying out science, by undertaking research – either by contracting it out toresearch organisations and consultancies or by doing it ourselves;

• Delivering information, advice, tools and techniques, by making appropriateproducts available to our policy and operations staff.

Steve KilleenHead of Science

Science Report Climate change impacts and water temperature iii

Executive SummaryGlobal average surface temperature has increased by 0.6°C during the twentieth century,providing clear evidence that climate change is occurring. It is likely that an increase in airtemperature will result in a corresponding increase in the water temperature of rivers and lakes.However, there is an overall lack of good quality, long-term water temperature monitoring datawith which to investigate such warming trends. This project aims to identify the available watertemperature datasets in England and Wales, and to compile a database containing all ongoingwater temperature monitoring. Statistical analysis of the database has been undertaken in orderto identify any recent annual or seasonal warming trends that might be attributed to climatechange. It was agreed by the project board that two examples of each Water FrameworkDirective (WFD) river type should be selected in each region in addition to one large river whichhad multiple sampling sites covering a range of WFD types between its upper and lower reaches.

In the first stage of the project, both Environment Agency and external sources of river and lakewater temperature data were investigated and all freely available records obtained wherepossible. These were audited for length, frequency and completeness of monitoring, beforeselection of sites for analysis. Some quality assurance procedures were also applied, such as theremoval of outlying data points. Six types of statistical analysis were performed on the selectedriver temperature datasets as follows:

1. Regional analysis. This analysis aims to uncover regional differences in river watertemperature. One main river in each of the eight Environment Agency regions wasselected to be included in the analysis.

2. Water Framework Directive (WFD) river type analysis within regions. This analysis aimsto uncover type-related differences in river water temperature within each region. Wherepossible, temperature records from two of each river type within each region wereincluded in the analysis.

3. WFD river type analysis between regions. This analysis aims to uncover region-relateddifferences in river water temperature within types. Where possible, two temperaturerecords from each region were included in each analysis.

4. Moving average analysis. This analysis was designed to look at any trends in meanmonthly and annual temperature over time for a number of sites on the same river.

5. Annual mean trend analysis. Assessment of the annual mean temperature series for thebest water temperature record in each region, including calculation of the rate of riverwater temperature change.

6. Seasonal analysis. Monthly temperature data, from a representative river in each region(with the exception of Anglian Region where two rivers were used), was split into winter,spring, summer and autumn seasons and moving average trend analysis performed toassess any changes in seasonal temperatures over time.

Significant differences in river water temperature between regions were revealed, with thehighest mean monthly water temperatures being found in the Thames Region (11.98°C) andAnglian Region (11.87°C) and the lowest in the North East Region (9.51°C). Within each region,river water temperatures also differ according to the WFD river typology. However, the watertemperature of all the river types included in the analysis differs between regions, suggesting thatthe influence of region (geographic location) on water temperature is often stronger than theinfluence of river type in England and Wales.

Moving average analysis and annual and decadal mean trend analysis have revealed anincrease in river water temperature over the last 20–30 years. This trend is particularly apparentin the Anglian, Thames and South West Regions, but is also seen in the lower reaches of mainrivers analysed in all regions. The highest water temperatures are nearly always seen in the later

Science Report Climate change impacts and water temperatureiv

part of the record, from 1990 to the present date. From the data available the analysis suggeststhat increases in river water temperature will be more noticeable in the south and east of the UKand in the lower reaches of rivers where increases in air temperature will be greater. However, itshould be noted that no upland rivers were represented in this analysis as there was notemperature data available for them.

Seasonal analysis revealed that winter river water temperatures in the northeast and northwest ofEngland were lower than those in the south, southeast and southwest of England. It alsoidentified a generally upward trend in river water temperatures in all seasons. There is someevidence that upper reaches of rivers (headwaters) are warming in winter and spring, whereaslower reaches are warming in summer.

There is an overall lack of long-term, continuous, quality-assured water temperature datasetsthroughout England and Wales particularly for upland rivers. It is therefore recommended thatexisting Environment Agency water temperature monitoring be improved, with emphasis ontargeted, automated, long-term monitoring at a selected number of sites in each region. Thecosts of setting up, maintaining and updating a water temperature database are estimated to bereasonably low. Other recommendations from the project include more detailed seasonalanalysis of river water temperatures and extension of the analysis to lake and estuarine sites.The potential for the air–water temperature relationship to be used both to reproduce historicalwater temperatures and to predict future water temperatures under a climate change scenarioshould also be investigated further.

Science Report Climate change impacts and water temperature v

ContentsExecutive Summary iii1 Introduction 11.1 Aims and objectives 11.2 Literature review 1

1.2.1 Introduction 11.2.2 Thermal regime 21.2.3 Water temperature models 51.2.4 Lakes and climate change 6

2 Methods 92.1 Data collection 9

2.1.1 Environment Agency datasets 92.1.2 External datasets 92.1.3 Air temperature data 10

2.2 Data processing 102.2.1 Assessing dataset quality 102.2.2 Assessing individual records 102.2.3 Location maps and typologies 12

2.3 Site selection 132.3.1 Selection of main rivers 132.3.2 Selection of river types 142.3.3 Selection of daily data 152.3.4 Selection of lake sites 16

2.4 Data analysis 162.4.1 Analysis of monthly data 162.4.2 Analysis of daily data 182.4.3 Infilling water temperature time series 18

3 Results and observations 273.1 Analysis of monthly data 27

3.1.1 Regional analysis 273.1.2 Type analysis within regions 273.1.3 Type analysis between regions 283.1.4 Moving average trends for each region 283.1.5 Annual mean and decadal trend analysis 353.1.6 Seasonal analysis 42

3.2 Analysis of daily data 493.2.1 Regional analysis 49

3.3 Infilling water temperature time series 493.4 Air temperature data 524 Analysis and discussion 534.1 Analysis of monthly data 53

4.1.1 Regional analysis 534.1.2 Type analysis within regions 534.1.3 Type analysis between regions 544.1.4 Moving average trends for each region 544.1.5 Annual mean and decadal trend analysis 544.1.6 Seasonal analysis 55

4.2 Analysis of daily data 564.2.1 Regional analysis 56

4.3 Infilling water temperature time series 564.4 Costs of external datasets 564.5 Maintenance of the archive 57

Science Report Climate change impacts and water temperaturevi

4.6 Gap analysis 575 Conclusions 596 Recommendations 60List of abbreviations 67Appendix A 68Appendix B 69Appendix C 81

Science Report Climate change impacts and water temperature vii

List of FiguresFigure 1.1 Daily water temperature variations on the River Tyne 3Figure 2.1 Location of temperature monitoring sites analysed in Anglian Region 19Figure 2.2 Location of temperature monitoring sites analysed in Midlands Region 20Figure 2.3 Location of temperature monitoring sites analysed in North East Region21Figure 2.4 Location of temperature monitoring sites analysed in North West Region22Figure 2.5 Location of temperature monitoring sites analysed in Southern Region 23Figure 2.6 Location of temperature monitoring sites analysed in South West Region24Figure 2.7 Location of temperature monitoring sites analysed in Thames Region 25Figure 2.8 Location of temperature monitoring sites analysed in Wales Region 26Figure 3.1 Anglian Region – River Stour moving average plots – upper, middle and lower

reaches 29Figure 3.2 Anglian Region – River Ouse moving average plots – upper, middle and lower

reaches 30Figure 3.3 Midlands Region – River Severn moving average plots – upper, middle and

lower reaches 31Figure 3.4 North East Region – River Tyne moving average plots – upper, middle and

lower reaches 31Figure 3.5 North West Region – River Ribble moving average plots – upper, middle and

lower reaches 32Figure 3.6 Southern Region – River Test moving average plots – upper, middle and lower

reaches 32Figure 3.7 South West Region – River Tamar moving average plots – upper, middle and

lower reaches 34Figure 3.8 Thames Region – River Thames moving average plots – upper, middle and

lower reaches 34Figure 3.9 Wales Region – River Dee moving average plots – upper, middle and lower

reaches 35Figure 3.10 Annual mean water temperature trends for benchmark sites 37Figure 3.11 Standard error plots for benchmark site annual temperature trends 39Figure 3.12 Decadal temperature change at benchmark sites, 1970–1980 40Figure 3.13 Decadal temperature change at benchmark sites, 1980–1990 41Figure 3.14 Decadal temperature change at benchmark sites, 1990–2000 41Figure 3.15 Upper reach sites winter 5-year moving average trends 42Figure 3.16 Lower reach sites winter 5-year moving average trends 43Figure 3.17 Upper reach sites spring 5-year moving average trends 44Figure 3.18 Lower reach sites spring 5-year moving average trends 44Figure 3.19 Upper reach seasonal comparisons for individual sites 46Figure 3.20 Lower reach seasonal comparisons for individual sites 48Figure 3.21 Regression analysis of River Wharf at Tadcaster (Type 13 North East Region)

versus River Derwent at Little Eaton (Type 13 Midlands Region) 50Figure 3.22 Regression analysis of River Irwell at Wark Weir (Type 13 North West Region)

versus River Churnet at Cheddleton Station (Type 13 Midlands Region) 51Figure 3.23 Regression analysis of River Thames at Abingdon (Type 8 Thames Region)

versus River Severn at Tewkesbury (Type 8 Midlands Region) 51Figure 3.24 Regression analysis of River Thames at Abingdon (Type 8 Thames Region)

versus River Severn at Haw Bridge (Type 8 Midlands Region) 52

Science Report Climate change impacts and water temperatureviii

List of tablesTable 2.1 Water temperature record scoring system 11Table 2.2 WFD river typology where temperature data available (from Environment Agency

river typology) 13Table 2.3 Main rivers selected by region 14Table 2.4 River types analysed within regions 14Table 2.5 River types analysed between regions 15Table 2.6 Daily temperature records analysed 16Table 3.1 ANOVA and Kruskal-Wallis test statistics – within regions 27Table 3.2 ANOVA and Kruskal-Wallis test statistics – between regions 28Table 3.3 Benchmark site information 36Table 3.4 Rate of decadal temperature change 40Table 3.5 Regression analysis results 50

Science Report Climate change impacts and water temperature 1

1 Introduction

1.1 Aims and objectivesEleven of the last twelve years (1995–2006) are ranked among the 12 warmest years sinceinstrumental records of global surface temperature began in 1850 (IPCC 2007). In addition,Karoly and Stott (2006) consider that the observed warming in annual mean central England airtemperature (CET) of approximately 1°C since 1950 is very unlikely to have been caused bynatural variations in climate. This provides clear evidence that climate change is occurring. TheUKCIP02 Climate Change scenarios indicate that, by the 2080s, the annual average temperatureacross the UK may rise between 1 and5°C depending on region and emissions scenario, with the greatest warming predicted in thesoutheast of the country in summer and autumn (Hulme et al. 2002). Changes to other climatevariables, such as precipitation, cloud cover, solar radiation, relative humidity and wind speed,are also predicted to occur. As a result, the Environment Agency needs to consider climatechange impacts and adaptation as part of all its activities.

Although the Environment Agency holds a considerable amount of long-term hydrometric,physicochemical and biological data for air, water and land, little analysis has been undertaken todetermine whether or not trends in environmental parameters can be attributed to climatechange. A report commissioned by the Environment Agency and published in 2003 described aninitial audit of Environment Agency datasets, listed key datasets external to the EnvironmentAgency with the potential to detect climate change impacts, and identified gaps in the availabilityof monitoring data (Codling et al. 2003). Water temperature was identified as being an importantclimate change indicator, with datasets that include water temperature measurements being heldboth within the Environment Agency and externally.

This project aimed to identify all of the available water temperature datasets in England andWales, and to compile a database containing all ongoing water temperature monitoring. It wasnot intended to be a detailed review of the effects of water temperature on ecology. The 'best'records in each Environment Agency region (generally the longest, the most frequently monitoredand the most complete) were subjected to statistical analysis to detect any long-term trends inwater temperature. Although water temperature datasets for both rivers and lakes are identified,freshwater river sites (excluding estuaries) are the main focus of the analysis.

The Countryside Council for Wales (CCW) has contributed both financially and practically to thisproject, and we thank them for their contribution.

1.2 Literature review

1.2.1 Introduction

Water temperature regimes in streams and rivers are influenced by changes in air and groundtemperatures as well as by alterations to the hydrological regime, all of which occur as a result ofboth natural and human modification. Water temperature has a strong influence on the physicalcharacteristics of streams and rivers, such as surface tension, density and viscosity, solubility ofgases and chemical reaction rates (Webb 1996, Webb and Nobilis 2007). Changes in watertemperature are therefore linked to changes in water quality (e.g. dissolved oxygenconcentrations and nitrogen levels). Statistical analysis of the effects of air temperature on river

Science Report Climate change impacts and water temperature2

water quality have shown that biological oxygen demand and suspended solids increase anddissolved oxygen concentrations decrease in response to an increase in air temperature (Ozakiet al. 2003). Lake water quality is also likely to be influenced by changes in water temperature. Amathematical lake water temperature model developed by Hassan et al. (1998a) showed thatwater temperature profiles change in response to higher air temperatures, which may lead toearlier stratification and corresponding changes in lake water quality. Deterioration of the waterquality in Lake Kasumigaura, Japan, has been found to correlate to increases in air temperature(Fukushima et al. 2000).

The ecological effects of changes in water temperature are outside the scope of this project, butshould be considered briefly here. Thermal regime influences aquatic organisms in terms ofgrowth rate, metabolism, reproduction and life history, distribution, behaviour and tolerance toparasites/diseases and pollution (Alabaster and Lloyd, 1980, Crisp 1996, Webb 1996, Caissie2006). Most communities and species in freshwater ecosystems are cold-blooded and willtherefore be sensitive to changes in the water temperature regime (Conlan et al. 2005). Theeffects of temperature change on the distribution, abundance and diversity, growth andreproduction of freshwater fishes have been particularly well documented. Davidson andHazlewood (2005) predict that future temperature increases are likely to have significant effectson the growth rate of freshwater fish, such as trout and salmon, in UK rivers. Similarly, Webb andWalsh (2004) have predicted that higher river temperatures as a result of climate change will bedetrimental to the habitat of cold water fish species such as Atlantic salmon, brown trout andgrayling, although warm water species may benefit.

1.2.2 Thermal regime

Streams and rivers show both temporal and spatial variations in water temperature. Temperatureat the source of a stream is generally close to that of groundwater temperature, and mean dailywater temperature increases with distance downstream or with increasing stream order. This rateof increase is greater for small streams than for large rivers. Smaller scale temperature variationscan be seen below the confluence with tributaries and in seepage areas in pools.

Water temperature also varies temporally on a daily and annual cycle. Over a 24-hour period,temperature is usually at a maximum in the late afternoon/early evening and at a minimum in theearly morning. Figure 1.1 shows an example of the daily cycle at a site on the River Tyne, plottedfrom hourly measurements taken on 3 June 2005, which broadly fits this pattern. Such variationsare generally smaller in cold headwater streams than in larger streams, as the groundwaterinfluence decreases. In terms of an annual cycle, the temperature of rivers in colder regions isgenerally close to freezing during the winter, with a sinusoidal annual temperature cycle fromspring to autumn (Caissie et al. 1998).


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When modelling river water temperature, heat exchange processes in the river environmentshould be taken into account (Caissie 2006). Changes in the water temperature of a watercourseoccur as a result of changes to the energy budget and/or thermal capacity. The energy or heatbudget of a stream or river reach can be expressed in terms of the following major components:

QaQfcQhbQhQeQrQn ±+±±±±=

where Qn = total net heat exchange, Qr = heat flux due to net radiation, Qe = heat flux due toevaporation and condensation, Qh = heat flux due to sensible transfer between air and water, Qhb= heat flux due to bed conduction, Qfc = heat flux due to friction, and Qa = heat flux due toadvective transfer in precipitation, groundwater, tributary inflows, streamflow and effluentdischarge. This equation represents the amount of energy available to modify the watertemperature of a stream or river. The thermal capacity of a watercourse depends on the volumeof water present, with heat storage capacity increasing and sensitivity to alterations in energybudget decreasing as the water volume increases (Webb 1996).

Solar radiation is generally thought to be the dominant component of the total energy flux. Netradiation (comprising solar radiation and net longwave radiation) was found to account for 56% ofthe total heat gain and 49% of the total heat loss for rivers in the Exe Basin, Devon (Webb andZhang 1997). Similarly, radiative fluxes were found to account for 85% of the total energy inputand 27% of the total energy losses to two Dorset chalk watercourses, the Piddle and Bere (Webband Zhang 1999).

Heat flux at the streambed is largely a function of geothermal heating (derived from the internalheat of the earth) through conduction and advective heat transfer from groundwater andhyporheic exchange. The majority of the total energy exchange within a river is thought to occurat the air/water interface, with a much smaller proportion occurring at the streambed/water


interface (Sinokrot and Stefan 1994, Evans et al. 1998). Evans et al. (1998) found that more than82% of total energy transfers in the River Blithe, Staffordshire, occurred at the air/water interfacewhereas only 15% occurred at the channel bed. However, heat exchange at the streambed/waterinterface has not been extensively studied, and there is uncertainty surrounding the relativeimportance of these processes (Caissie 2006).

Natural and anthropogenic modifications to the river heat budget can result in changes to thethermal regime. The more common types of modification (predominantly anthropogenic) are asfollows:

1. Land use changes. Changes in vegetation cover and land management techniques mayaffect hydrology and water quality and therefore potentially the water temperature ofrivers and lakes. These include land drainage, agricultural soil erosion, forestry(considered separately below) and urban development (Robinson et al. 2000).

2. Forestry/removal of cover. The removal of riparian tree cover will generally result in an

increase in river water temperature due to an increase in the amount of shortwave solarradiation reaching the river channel (Sinokrot and Stefan 1993). A study of the effects ofafforestation on stream temperatures in southwest Scotland suggests that shading ofincoming solar radiation has a strong effect on the water temperature behaviour of aforested stream (Webb and Crisp 2006). With the use of modelling, Bartholow (2000)found a net effect from clearcutting of a 4°C warming, with changes in stream shadingbeing the largest influence on maximum daily water temperature. Over a 30-year periodbetween 1955 and 1984, Beschta and Taylor (1988) found that average daily maximumand minimum stream temperatures have increased by 6 and 2°C, respectively.

3. Flow and abstraction. The effect of river flow on water temperature is dependent on

channel shape and the surface area of the water. If the surface area remains similar butthe flow is reduced, water temperature will increase during hot and sunny weather(Solomon 2005). Similarly, abstraction might alter the volume and/or velocity of waterflowing in the channel and cause changes in water temperature by the same mechanisms(Webb 1996). However, the effect of abstraction will vary according to the river type; forexample, groundwater abstractions in the upper catchment are likely to have the greatestimpact on water temperature in groundwater-fed chalk streams (Solomon 2005).

4. Flow regulation. River regulation by upstream dams and reservoirs directly impacts the

downstream water temperature regime. If the flow regime of the river is also altered on adaily basis, this might influence water temperature as a result of higher or lower flows(Webb 1996). Webb and Walling (1997) analysed 14 years of water temperature databelow a reservoir in southwest England, and concluded that the main effects of regulationwere to increase mean water temperature, depress summer maximum values, eliminatefreezing conditions, delay the annual cycle and reduce daily fluctuation. However, theseeffects might vary, with a decrease in water temperature occurring if water is releasedfrom deep in the reservoir where it is coldest. Channelisation and other types of flowregulation might also have significant impacts on thermal capacity. For example,augmentation of flows by cold groundwater can bring about a reduction in river watertemperature (Cowx 2000).

5. Heated effluents. A significant volume of heated effluent is returned to rivers following

abstraction for cooling purposes during electrical power generation (Webb 1996) andother industrial processes. The quantity and spatial distribution of thermal effluents havechanged significantly in recent years and need to be accounted for when interpretingtemperature records. Thermal discharges will have a greater effect on water temperaturewhen river discharge is low (Solomon 2005) and can increase river temperature by


several degrees, often affecting oxidation rates and the solubility of gases (Alabaster andLloyd 1980).

6. Climate change. Water temperature is known to respond to air temperature, with a

strong linear correlation between the two at temperatures greater than 0°C (Crisp andHowson 1982, Stefan and Preud'homme 1993, Mohseni and Stefan 1999, Erickson andStefan 2000). Air temperatures are predicted to increase over the coming years as aresult of global warming, and this is likely to result in a corresponding increase in watertemperature. For example, analysis of a 30-year record of water temperature fromScotland suggested that mean daily maximum temperatures in winter and spring haveincreased with time as a result of changes in climate (Langan et al. 2001), and Webb andNobilis (2007) found a significant increase (0.8°C) in monthly mean river watertemperatures in Austrian rivers over the twentieth century, and particularly since 1970.The pattern of the North Atlantic Oscillation (NAO) is also known to influence the climate,and Webb and Nobilis (2007) found that both water and especially air temperatures inAustria showed statistically significant correlations with the NAO index. It should be notedthat in comparison with the previous 130 years, the positive phase of the NAO seenduring the 1990s was unprecedented and it is suggested that external forcing of theclimate (e.g. solar irradiation, stratospheric ozone levels) may be responsible (Osborn2004). Changes in water temperature as a result of climatic warming have been projectedusing various modelling techniques. These are described in Section 1.2.3 below.

1.2.3 Water temperature models

Water temperature can be modelled using a variety of techniques. These can be classified intothree groups: regression modelling, stochastic modelling and deterministic modelling (Caissie2006). These range in complexity from simple regression models to elaborate deterministicapproaches that take into account all relevant heat fluxes at the water surface and at thesediment/water interface (Caissie et al. 2005).

Estimation of stream temperature from air temperature by linear regression is a popular methodbecause only one input variable (air temperature) is required. Water temperature has beensuccessfully predicted with simple linear regression models using weekly or monthly airtemperature as the input parameter (Mackey and Berrie 1991, Stefan and Preud'homme 1993,Webb and Nobilis 1997). For example, Crisp and Howson (1982) developed a water temperaturemodel based on a 5-day and 7-day mean water temperature that explained 86–96% of thevariability in water temperature. However, Morrill et al. (2005) evaluated the relationship betweenair temperature and stream temperature for a geographically diverse set of streams and foundthat very few streams showed a linear air–water temperature relationship. A nonlinear modelproduced a better fit than a simple linear model for most of these streams.

The time lag between a change in air temperature and a corresponding change in watertemperature ranges from 4 hours for shallow rivers (less than 1 metre deep) to 7 days for deeperrivers (~ 5 metres deep) (Stefan and Preud'homme 1993). These authors showed thatincorporating a time lag into the regression analysis improved the estimation of daily watertemperatures from air temperatures. Investigation of the air–water temperature relationship in theExe Basin, Devon, also found that the power of a simple regression model based on hourly datawas improved by the incorporation of a lag (Webb et al. 2003). Multiple regression models can beused to incorporate other explanatory variables, such as time lag data, river discharge, depth ofwater etc, into the model (Caissie 2006).

Both stochastic and deterministic models have been used to model water temperature for dailytime steps and have similar modelling performances. Stochastic models often involve theseparation of the water temperature time series into the long-term annual component and the


short-term component and can provide good predictions of daily water temperature (Caissie et al.1998, 2001). Deterministic models aim to quantify the total energy flux of the river and then fit thetotal energy flux to observed changes in water temperature. They are therefore often applied tocomplex problems such as the impact of thermal effluent discharges on the temperature ofreceiving waters. However, deterministic models are more complicated than stochastic models,requiring input of all relevant meteorological data in addition to air temperature (Caissie 2006).

Different time-scales will result in different air–water temperature relationships, as will differencesin stream type, such as groundwater-dominated versus non-groundwater-dominated streams(Caissie 2006). For example, the thermal regime of chalk streams is different from that of otherrivers due to the stabilising influence of groundwater discharge. A study of four English chalkstreams with a large groundwater component confirmed these differences and concluded that,while air temperature is a good indicator of the thermal regime of a river, groundwater-dominatedstreams such as chalk streams should be considered separately from other stream types(Mackey and Berrie 1991). This study also suggested that chalk streams are less likely to beaffected by climatic changes than other types of river and is in agreement with previouspredictions of stream water temperature on a chalk stream, the Lambourn, and the Water of Leith(Smith 1981).

Several authors have looked at the potential for using air temperature to predict streamtemperatures under a global warming scenario. Mohseni and Stefan (1999) examined the validityof using linear extrapolation to project stream temperatures under a warmer climate. At moderateair temperatures of between 0 and 20°C, the air–water temperature relationship was found to belinear. However, at low air temperatures this relationship is flat and at high air temperatures it hasa moderate slope with a tendency towards levelling off. The overall relationship between streamtemperature and air temperature therefore resembles an S-shaped function. The studyconcluded that linear regression models will not accurately predict stream temperatures at highair temperatures and are therefore not suitable for projecting the effects of warming due toclimate change.

A four-parameter nonlinear function of weekly air temperatures was used by Mohseni et al.(1999) to project changes in mean weekly stream temperatures in response to global warming.Weekly air temperature data from 166 weather stations were incremented by the output of theCanadian Center of Climate Modelling (CCC) general circulation model (GCM) and applied tononlinear stream temperature models developed for 803 gauging stations. Mean annual streamtemperatures in the USA were predicted to rise by 2–5°C at 764 of these gauging stations, withno significant changes being seen at the remaining 39. Similarly, temperatures in Minnesota areprojected by the CCC GCM to rise by 4.3°C during the summer season, translating to an averagerise of 4.1°C in stream temperature (Pilgrim et al. 1998).

Good air temperature records are more readily available than good water temperature records,and have therefore frequently been used to predict river water temperatures. However, there arecomplications with this method as discussed, particularly associated with the projection of watertemperature increases under a climate change scenario. It is difficult for any model to accuratelysimulate events outside the range of the calibration set, such as the extreme temperaturesexpected under a climate change scenario. Therefore, while the air–water temperaturerelationship may be useful for infilling gaps in a water temperature record, actual measured watertemperature records are preferable for monitoring and estimating climate change and arerequired to evaluate the impact of climate change effectively.

1.2.4 Lakes and climate change

Deep lakes are considered to be good indicators of climate change (Dokulil et al. 2006) based onlong-term changes in ice cover, surface temperature and mixing regimes (Salmaso et al. 2003,


Johnson and Stefan 2006). For example, Magnuson et al. (2000) found consistent evidence oflater freezing (5.8 days per 100 years later) and earlier thaw (6.5 days per 100 years earlier) ofice on lakes and rivers in the Northern Hemisphere from 1846 to 1995. The appearance of ice onLake Windermere is used by Defra as a climate change indicator, and in recent years highvalues of the NAO index have resulted in mild winters and few days with ice cover on the lake.However, it is not yet known whether or not this is an aberration or the beginning of a new trend.

Livingstone (2003) identified strong climate-related mean water temperature increases in monthlytemperature profiles from Lake Zurich, Switzerland, over a 52-year period. A 20% increase inthermal stability and a 2–3-week extension in the stratification period of this lake have resultedfrom the high rates of warming seen between the 1950s and 1990s. Similarly, Carvalho andKirika (2003) observed an increase in annual mean temperature in Loch Leven of approximately1°C over a 34-year period, with greater increases occurring during winter and spring periods.

Changes in climate variables such as precipitation, wind speed, solar radiation and airtemperature as a result of global climate change will have a direct influence on lake water quality,potentially resulting in changes to lake water quality (Hassan et al. 1998b). This effect may varyin magnitude depending on the physical character of the lake in question; for example, modellinghas shown that in eutrophic lakes with long water residence times, high phosphorusconcentrations and therefore high phytoplankton production may become a problem under aclimate warming scenario (Malmaeus et al. 2006). Statistical analysis of the relationship betweenmeteorological conditions and lake water quality over a 17-year period showed that water qualityindicators such as increased chemical oxygen demand and decreased transparencycorresponded to an increase in air temperature (Fukushima et al. 2000). Changes in air/lakewater temperature and temperature stratification dynamics can therefore have a significantimpact on biological and chemical processes within lakes.

The effects of global warming on lake and reservoir ecosystems have been simulated using acombined water temperature–ecological model (Hosomi et al. 1996). This model was applied toLake Yunoko, Japan, and changes in the water temperature and quality were simulated inresponse to a 2–4°C rise in air temperature. The results indicate that in response to this airtemperature increase, nutrient concentrations in the bottom water will increase, phytoplanktonwill increase in concentration at the beginning of autumn, and phytoplankton species compositionwill change. Lake water temperature has also been successfully simulated by several others(Hondzo and Stefan 1993, Rasmussen et al. 1995, Antonopoulos and Gianniou 2003, Fang et al.2004).

Fluctuations in the NAO have a strong influence on lakes in North America and Europe (Georgeet al. 2004, Dokulil et al. 2006, Webb and Nobilis 2007). Temperatures in the hypolimnion (thebottom waters of a thermally stratified lake) of 12 deep European lakes were observed to rise inall lakes by approximately 0.1–0.2°C per decade and were predicted most consistently by themean NAO index for January to May (Dokulil et al. 2006). This temperature rise affects mixingconditions, thermal stability and oxygen concentrations within the lake. In agreement with this,George et al. (2004) found that air temperature and lake surface and bottom temperatures of fourEnglish Lake District lakes showed a strong positive correlation with the NAO index and alsoinfluenced winter nitrate concentrations and phytoplankton growth. This effect was particularlypronounced in smaller or shallower lakes. Again, it is difficult to distinguish whether or not therecent sequence of warm years is the beginning of a new trend or simply part of a natural cycle,but the influence on water temperatures can be significant.



2 Methods

2.1 Data collectionThe first and most critical stage of the project involved the identification and acquisition ofrelevant freshwater temperature datasets. Potential sources were identified to be data alreadycollected and held by the Environment Agency, or data available from external organisationssuch as water companies and universities. Datasets from both rivers and lakes were requested.To facilitate the process, a Data Request Form was devised and sent to all contacts with theinitial data request, as reproduced in Appendix A. This asked for detailed information on thedatasets held, enabling an informed decision to be made regarding suitability for inclusion in theanalysis.

2.1.1 Environment Agency datasets

The Environment Agency project team acted as the main source of internal contacts fortemperature data already held within the Environment Agency. Regional contacts wereapproached in the first instance, and the request passed on to others as appropriate. The largestsingle source of data was the Environment Agency's Water Information Management System(WIMS) database, which holds thousands of records for each of the eight Environment Agencyregions. All freshwater temperature records from this database were passed to Entec in the formof an Access database containing tables of regional data, which was queried in order tosummarise sites by length of record, sampling frequency and waterbody type (river or lake).

In addition, individual temperature records held within the Environment Agency outside WIMS(regional monitoring, the Water Information Management System Kisters (WISKI) database etc)were also listed and sourced where appropriate. Many of these had not been quality assured andtherefore required a significant amount of checking before they could be used. These datasetsranged in size from single records to quite large databases containing records for many sites,such as the Tideway Information Management System (TIMS) received from the ThamesRegion. Regional summaries listing all water temperature data sources identified during thisproject can be seen in Appendix B.

2.1.2 External datasets

External sources of water temperature data were identified using Entec and Environment Agencyknowledge and were contacted by Entec with a request to complete the Data Request Form.Organisations contacted included the Centre for Ecology and Hydrology (CEH), the CountrysideCouncil for Wales (CCW), the Freshwater Biological Association (FBA), the Natural EnvironmentResearch Council (NERC) Environmental Change Network (ECN), the major water companies(Anglian Water, Thames Water, Southern Water etc), and several universities. Cost was animportant consideration when considering data held by external organisations, as many will notrelease data without a charge. Every effort was therefore made to record the quality of datasetsthat were not freely available, so that their value could be accurately assessed. All knownavailable datasets and associated costs have been recorded as part of the project output and arelisted in the regional summary tables in Appendix B.It should be noted that there are a number of 'Lake Dynamics Monitoring Stations' (LDMSs)located in the Wales and North West Regions. CEH had funding to build buoys and develop thetechnology to monitor water chemistry and temperature in lakes. However, the funding to deploy,run and co-ordinate the results from them, has not yet been made available. Currently a number


of different universities are collecting data from the buoys, but the co-ordination of the results hasyet to occur.

2.1.3 Air temperature data

The cost of sourcing Met Office air temperature data to cover all regions was investigated. Airtemperature data could potentially be used to hindcast river water temperatures to infill gaps in atemperature record, or to extend a record further back in time than the first recordedmeasurement. Air temperatures have also been used to predict future water temperatures incases where air temperature data are more readily available than water temperature data.

2.2 Data processing

2.2.1 Assessing dataset quality

All WIMS river and lake records were extracted from the Access database to produce a full list ofsites for each Environment Agency region including site name, grid reference, first and lastsampling date, and the number of samples taken during this period. The first and last samplingdates were converted to a sampling duration (in days), which was then used to sort the recordsby length. This information was used to calculate an average sampling frequency by dividing thesampling duration (in days) by the total count of samples taken for that record. This calculatedfrequency was an average value and might also include sampling frequencies significantly higheror lower than the average, as well as gaps in the time series. However, it represented a fast andreasonably accurate method with which to reduce the number of records under consideration.Generally, any site with a sampling frequency of greater than 15 days (a fortnight) was deleted,although for regions in which the number of sites with high frequency sampling was limited (e.g.Wales) some sampling frequencies that would otherwise have been rejected were retained.

For individual records not in the WIMS database, a preliminary decision on their value was madeon the basis of information given on sampling frequency and record length and completeness asstated by the respondent on the Data Request Form. All suitable records that were freelyavailable were obtained in full, and taken to the next stage of assessment with the retainedWIMS records (Section 2.2.2).

2.2.2 Assessing individual records

All records remaining after this processing were extracted in full from the WIMS database orobtained from the data owner and subjected to further analysis. Some quality assuranceprocedures were carried out at this stage, with outlying temperature values being removed fromthe time series and sites with any known artificial influences (e.g. discharges, water transfers)being excluded. However, it was not within the remit of this project to undertake detailed qualityassurance. In addition, it should be noted that the rivers and sites included in the analysis will besubject to many artificial influences that could affect water temperature (e.g. discharges, watertransfer schemes, regulation releases). Regional knowledge is required to identify sites that aresubject to such influences.

A scoring system was applied to each record to generate a final number for comparison withother records. Each temperature measurement was given a score based on the time that hadelapsed since the previous measurement, as follows:

1. a gap of 8 days or less between samples scored 10;


2. a gap of 9 to 17 days scored 8;3. a gap of 18 to 39 days scored 6;4. a gap of 40 to 59 days scored 2;5. a gap of greater than 60 days scored 0.

The total score for the record was then summed to give a final score that reflected the length andcompleteness of the record as well as the sampling frequency. Table 2.1 shows an example ofthis scoring system from a site in the Anglian Region.

The final output of this process for each of the eight regions was a list of river sites and a list oflake sites, giving a total of 16 tables. These tables contained the sites short-listed in Section2.2.1 and for each site included the river WFD typology, details of first and last sampling dates,missing data, the score as generated above, and a weighted score generated by dividing thisscore by the number of months of temperature data available for the site. This information wasused to select sites to be included in the analysis as described below (Section 2.3).

Table 2.1 Water temperature record scoring system

Sample name Sample date Sample time Temperature Days tonextsample

Score

R.Can BeachesMill

21-Jan-04 0945 7.80 26 6

R.Can BeachesMill

16-Feb-04 1135 7.16 30 6

R.Can BeachesMill

17-Mar-04 1210 12.60 34 6

R.Can BeachesMill

20-Apr-04 1135 9.47 42 2

R.Can BeachesMill

01-Jun-04 1035 15.18 6 10

R.Can BeachesMill

07-Jun-04 1100 17.84 30 6

R.Can BeachesMill

07-Jul-04 1130 16.24 30 6

R.Can BeachesMill

06-Aug-04 1155 20.15 45 2

R.Can BeachesMill

20-Sep-04 1210 14.54 28 6

R.Can BeachesMill

18-Oct-04 1120 10.55 22 6

R.Can BeachesMill

09-Nov-04 1135 10.67 30 6

R.Can BeachesMill

09-Dec-04 1105 7.40 49 2

R.Can BeachesMill

27-Jan-05 1450 4.60 42 2

R.Can BeachesMill

10-Mar-05 1200 6.20 26 6

R.Can BeachesMill

05-Apr-05 0955 9.20 41 2


Sample name Sample date Sample time Temperature Days tonextsample

Score

R.Can BeachesMill

16-May-05 1205 12.75 24 6

R.Can BeachesMill

09-Jun-05 1140 14.54 28 6

R.Can BeachesMill

07-Jul-05 1105 5.58 33 6

R.Can BeachesMill

09-Aug-05 1140 15.22 28 6

R.Can BeachesMill

06-Sep-05 1134 18.27 17 8

R.Can BeachesMill

23-Sep-05 1147 14.33 25 6

R.Can BeachesMill

18-Oct-05 1158 12.61 24 6

R.Can BeachesMill

11-Nov-05 1156 11.41 18 6

R.Can BeachesMill

29-Nov-05 1254 4.35 Total 124

2.2.3 Location maps and typologies

All sites that made it through the initial selection process described in Section 2.2.1 wereimported onto a GIS map, with separate maps being produced for each region. A WFD rivertypology was assigned to each of the mapped sites for use in the selection of river types foranalysis (Section 2.3.2). Table 2.2 provides a full description of the WFD river typology (Defra2005). This table was derived from the Water Framework Directive (WFD) ArcView GIS shapefileprovided by the Environment Agency. It should be noted that there are no upland rivers (i.e.those > 800 m high) in this dataset.


Table 2.2 WFD river typology where temperature data available (from EnvironmentAgency river typology)

Catchment altitude Catchment geology Catchment size Type

Low Si S 1Low Ca S 2Low Or S 3Low Si M 4Low Ca M 5Low Or M 6Low Si L 7Low Ca L 8Mid Si S 10Mid Ca S 11Mid Or S 12Mid Si M 13Mid Ca M 14Mid Or M 15Mid Si L 16Mid Ca L 17Low Sa S 28Low Si XS 37Mid Si XS 38Low Ca XS 40Low Or XS 43

Altitude: Low < 200 m, Mid 200–800 m, High > 800 m (not represented in this dataset);Geology: Si siliceous, Ca calcareous, Or organic, Sa salt; Size: XS < 10 km2, S 10–100 km2, M100–1000 km2, L 1000–10,000 km2

2.3 Site selection

2.3.1 Selection of main rivers

Within each region, one main river was chosen as the focus of the analysis. Within AnglianRegion, the Ouse was included in addition to the Stour, so that the pattern of temperaturechange within a river subject to flow modification could be explored. The rivers to be used werechosen with reference to the list of sites and scores previously created, with the aim of selectingthe river within each region with the highest possible number of long-term temperature records. Ifdaily data from a main river had been collected, wherever possible this was the river selected forthe main river analysis. Following selection, the original database was revisited in order to gatherall the additional temperature records for each river. Only sites at which temperature monitoringis still ongoing were included in the analysis.


The main rivers selected for each region are shown in Table 2.3. Figures 2.1 to 2.8 show thelocations of all the sites analysed in each region.

Table 2.3 Main rivers selected by region

Region River Types included*

Anglian Stour and Ouse 2, 5, 8Midlands Severn 7, 8, 10, 13North East Lower Tyne and Tyne 2, 11, 14North West Ribble 11, 14, 17Southern Test 5, 8South West Tamar 1, 4Thames Thames 5, 8Wales Dee 13, 17* Refer to Table 2.2 for a description of typologies

2.3.2 Selection of river types

As far as possible, two examples of each river type present in each region were included in theanalysis. Again, these were selected using the list of sites and scores, so that for each river typethe longest and most frequently monitored sites were used. Therefore, it was not always possibleto include all types in the analysis due to lack of suitable temperature datasets. Table 2.4 showsthe river types selected and analysed within each region, and Figures 2.1 to 2.8 show the sitelocations.

Table 2.4 River types analysed within regions

Region Types analysed* Rivers included

Anglian 1, 2, 3, 5, 6, 8, 40 Stour, Ouse, Hundred Foot, Thurne,Whittlesey Dyke, Bevills Leam,Blackwater, Chelmer, Forty Foot, Nene,Ramsey, Spickets

Midlands 1, 2, 4, 5, 7, 8,10, 11, 13, 14, 17, 40 Strine, Rea Brook, Erewash, Camlad,Trent, Idle, Soar, Afon Clywedog,Severn, Wye, Morda, Derwent,Churnet, Dove, Marton Drain, DimoreBrook

North East 1, 2, 4, 5, 8, 10, 11, 12, 13, 14, 17 Coquet, Oak Beck, Doe Lea, Dove,Blyth, Wansbeck, Hull, Dearne, Ouse,Aire, Holme, Little Don, Don, Dibb,Lewisburn, Wharfe, Calder, Tees

North West 1, 2, 4, 5, 8, 10, 11, 12, 13, 14, 15,16, 17, 28

Roe, Ive, Irk, Yarrow, Wyre, Darwen,Irwell, Alt, Mersey, Weaver, Esk,Ogden, Chew Brook, Etherow, Leven,Calder, Ribble, Lune, Petteril, RookeryBrook

Southern 1, 2, 4, 5, 8, 37, 40 Wallers Haven, Arun, Rother, Ouse,


Region Types analysed* Rivers included

Uck, Lymington, Cuckmere,Blackwater, Test, Botley Stream, BroadRife, Chichester Canal

South West 1, 2, 4, 5, 7, 8, 10, 11, 13 Carnon, Wolf, Brit, Tamar, Lyd, Axe,Exe, Alphin Brook, Avon, Erme,Walkham, Culm, Tavy, Plym

Thames 1, 2, 4, 5, 8, 11, 40 Boveney Ditch, Thames, Blackwater,Hogsmill, Cherwell, Wey, Lee, Colne,Eye, Churn, Beam

Wales 1, 2, 4, 5, 10, 11, 13, 14, 16, 17 Llan, Gwenfro, Clywedog, Rhymney,Cleddau, Loughor, Ely, Afan, Seiont,Afon Llwyd, Tawe, Ogmore, Alyn,Neath, Tywi, Gwili, Dee, Wye

* Refer to Table 2.2 for a description of typologies

For the analysis of river types between regions, only types found in more than one of the eightregions could be included in the analysis. These types are shown in Table 2.5, and the sitelocations can be seen in Figures 2.1 to 2.8.

Table 2.5 River types analysed between regions

River type Regions analysed*

1 A, M, NE, NW, S, SW, T, W2 A, M, NE, NW, S, SW, T, W4 M, NE, NW, S, SW, T, W5 A, M, NE, NW, S, SW, T, W8 A, M, NE, NW, S, SW, T10 M, NE, NW, SW, W11 M, NE, NW, SW, T, W13 M, NE, NW, SW, W14 M, NE, NW, W17 M, NE, NW, W40 A, M, S, T* Regions are labelled as follows: A = Anglian; M = Midlands; NE = North East; NW = NorthWest; S = Southern; SW = South West; T = Thames; W = Wales

2.3.3 Selection of daily data

Daily data were received for four regions: Midlands, North East, Thames and Wales. The riversthat were included in the daily analysis are shown in Table 2.6, and are mapped in Figures 2.1 to2.8.


Table 2.6 Daily temperature records analysed

Region Sites analysed Types included

Midlands Afon Clywedog, Severn, Teme, Vyrnwy 7, 8, 10, 13North East Humber, Ouse, Tyne 2, 5, 14, 17Thames Kennet, Lee, Loddon, Pymmes Brook,

Thames, Wey2, 4, 5, 8

Wales Dee, Taff, Tywi, Wye 10, 13, 16, 17

The water temperature data for Thames, Wales and North East Regions was supplied as sub-daily data, whereas the Midlands Region data were supplied as daily mean values. An Excelmacro was used to convert sub-daily data to a mean daily time series and to infill any missingdays.

2.3.4 Selection of lake sites

Due to time constraints and lack of readily available lake temperature records, the statisticalanalysis was limited to river water temperature data only, as described in Section 2.4 below. Alist of lake temperature records identified as part of the data collection exercise can be found inAppendix B.

2.4 Data analysisStatistical analysis of the water temperature data was carried out using SPSS software. Althoughthe Kolmogorov-Smirnov test for normality showed that the temperature data were not normallydistributed, Analysis of Variance (ANOVA) was used based on the principle that ANOVA is robustto departures from normality, particularly when sample sizes are large (Stevens 1996, Gravetterand Wallnau 2000). Similarly, although Levene's test for homogeneity of variances showedvariances to be unequal, it is considered that ANOVA is robust to the violation of this assumptionwhen group sizes are approximately equal (e.g. largest/smallest = 1.5) (Stevens 1996). Groupsizes were checked for all tests, and most were approximately equal. However, any single groupwithin a test that was smaller than the others was considered to be unsuitable for analysis andexcluded from the dataset. Similarly, where any single group was considerably larger than theothers, temperature records were excluded on a site by site basis to reduce the dataset size andeliminate bias.

To further verify the results, the Kruskal-Wallis test was run on the same data. This is a non-parametric test that does not assume a normal distribution or equal variances. The results of alltests in terms of significance were the same, leading to the conclusion that in this case ANOVAwas robust.

Taking the above into account, post hoc analysis using Tukey's Honestly Significant Differencetest (HSD) was also carried out in order to identify any differences in water temperature betweengroups. Although this test carries the same assumptions as ANOVA, for the reasons statedabove it was considered suitable to use for the purposes of this analysis.

2.4.1 Analysis of monthly data

All sites monitored less frequently than daily were included in this analysis (e.g. weekly,fortnightly and monthly). All temperature records to be analysed were converted to a time seriesof monthly mean values, and months during which no temperature had been recorded were


infilled with a specified value (-9999) to produce a standardised monthly time series for statisticalanalysis using SPSS. It should be noted that records were not audited to take account of the timeof day at which temperature measurements were taken. As river water temperature variestemporally on a daily cycle, the point in the cycle at which a measurement is taken may affectweekly and monthly temperature means calculated from the data.

The locations of the monthly temperature records analysed in each region are shown in Figures2.1 to 2.8, and a full list of all the sites included in the analysis is given in Appendix C.

Six different analyses were carried out on the monthly data:

1. Regional analysis. This analysis aims to uncover regional differences in watertemperature; for example, is river water temperature in Anglian Region different from riverwater temperature in Wales? Monthly temperature data from the main river in each of theeight regions were included in the analysis: Anglian, Midlands, North East, North West,Southern, South West, Thames and Wales.

2. Type analysis within regions. This analysis aims to uncover type-related differences in

water temperature within each region; for example, is the temperature regime of aThames Region Type 2 river different from a Thames Region Type 5 river? As far aspossible, monthly temperature records from two of each river type within each regionwere included in this analysis.

3. Type analysis between regions. This analysis aims to uncover region-related differences

in water temperature within types; for example, is the temperature regime of a Type 2river in Thames Region different from the temperature regime of a Type 2 river in Wales?As far as possible, two monthly temperature records from each region were included ineach analysis.

4. Moving average analysis. This analysis was designed to look at any trends in

temperature over time for a number of sites on the same river. To achieve this, the mainriver sites selected for each of the regions were utilised. The monthly temperature datawere plotted for all sites and moving average (12-month) trendlines were displayed for anumber of selected sites on each river: one in the upper reach, one in the middle reachand one in the lower reach.

5. Annual mean trend analysis. Assessment of the mean annual trend in water temperature

of the best site in each region. The best site was selected with regard to length andcompleteness of record and frequency of monitoring, as previously assessed by thescoring system in Section 2.2. The rate of annual mean river water temperature change(°C per decade) was also calculated for each selected site and compared with the rate ofair temperature warming shown by the Hadley Centre Central England Temperature(HadCET) dataset (Parker et al. 1992).

6. Seasonal analysis. The monthly data were divided into seasonal data. Winter was

represented by January–February–March temperatures, spring was represented by April-May-June, summer was represented by July–August–September and autumn byOctober–November–December. The three months of temperature data were thenaveraged to give a single figure for the season. The seasonal data were graphed and a 5-year moving average trendline plotted. In addition, the raw seasonal data were plotted foreach of the main rivers in each region for an upper reach site and a lower reach site.


2.4.2 Analysis of daily data

All daily and sub-daily temperature records to be analysed were converted to a time series ofdaily mean values, and missing days were infilled with a specified value to enable recognition ofnull values during the statistical analysis. This produced a standardised daily time series for entryinto the SPSS statistical software.

The daily temperature data were analysed for differences between regions. Daily data were onlyobtained for four regions: Midlands, North East, Thames and Wales. Therefore, there were notenough data available to allow for a meaningful comparison of types within or between regions.Figures 2.1 to 2.8 show the location of the daily temperature records analysed in each region,and a full list of all the sites included in the analysis for each region is given in Appendix C.

2.4.3 Infilling water temperature time series

The water temperature datasets in some regions such as Thames, North West and North Eastbegin in the early 1970s, whereas the Midlands and Anglian monthly data do not start until themid 1980s. Regression analysis was therefore trialled to ascertain whether or not temperaturedata from one region could be used to produce a historical time series for another region. Suchtechniques can have wide-ranging applications: for example, infilling and reconstructiontechniques have previously been used to extend river flow records using rainfall data (Jones etal. 2006).





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3 Results and observations

3.1 Analysis of monthly data

3.1.1 Regional analysis

Statistical analysis using both ANOVA and the nonparametric Kruskal-Wallis test revealed thereto be significant differences in river water temperature between the eight regions (p < 0.01). Asignificance level of p < 0.05 was used throughout the analysis. Tukey's post hoc test (used todetermine where significant differences lie) revealed statistically significant differences in watertemperature between most combinations of regions except for Anglian and Thames, Midlandsand Southern, Midlands and South West, Midlands and Wales, and Southern and South West.Substituting the Ouse for the Stour as the main river in Anglian Region does not change thisresult.

The highest mean water temperatures for the whole temperature dataset were recorded in theThames and Anglian Regions (11.98 and 11.87°C, respectively) and the lowest in the North EastRegion (9.51°C).

3.1.2 Type analysis within regions

ANOVA revealed significant differences in mean water temperature for the whole datasetbetween river types within all regions apart from Anglian Region (p < 0.01). The results of theKruskal-Wallis test confirm these differences. Table 3.1 shows these results in addition to theresults of Tukey's post hoc test.

Table 3.1 ANOVA and Kruskal-Wallis test statistics – within regions

Region ANOVA Kruskal-Wallis Tukey's post hoc

Anglian 0.589 0.807 No significant differences between types*Midlands 0.000 0.000 Significant differences between most typesNorth East 0.000 0.000 Significant differences between most typesNorth West 0.000 0.000 Significant differences between many types:

type 8 is different from all othersSouthern 0.000 0.000 Significant differences: type 1 and 5; 37 and 1,

2, 4; 40 and 1, 2, 4, 8South West 0.000 0.000 Significant differences: type 1 and all others;

11 and 1, 2, 4, 5, 7, 8; 10 and 7, 8; 13 and 7, 8Thames 0.000 0.000 Significant differences: type 4 and 5, 8, 40; 11

and 1, 2, 4, 5, 8, 40Wales 0.000 0.004 Significant differences: type 1 and 11, 13; 5

and 11, 13; 11 and 17

*Refer to Table 2.2 for a description of typologies


3.1.3 Type analysis between regions

ANOVA revealed significant differences in water temperature of the same river type betweendifferent regions (p < 0.05). Again, the results of the Kruskal-Wallis test confirm thesedifferences. Table 3.2 shows these results in addition to the results of Tukey's post hoc test.

The river types 12 and 16 were only present in two regions, therefore the t-test was used toanalyse these types instead of ANOVA. The results showed a significant difference in Type 12water temperature data between North East and North West Regions (p < 0.01), but nodifference in Type 16 data between North West and Thames Regions.

Table 3.2 ANOVA and Kruskal-Wallis test statistics – between regions

River type ANOVA Kruskal-Wallis Tukey's post hoc

1 0.000 0.000 Significant differences between most regions*,especially SW and all others

2 0.000 0.000 Significant differences: A and NE, NW, S, SW,T; W and NE, NW, S, SW, T

4 0.000 0.000 Significant differences: NE and NW, S, SW, T,W; NW and SW, W

5 0.000 0.000 Significant differences: W and M, NE, NW, S,SW, T

8 0.000 0.000 Significant differences: NW and A, NE, S, SW;S and W

10 0.000 0.000 Significant differences: M and NE, SW, T; NWand NE, SW, T

11 0.000 0.000 Significant differences: NE and SW, T, W; NWand SW, T, W;

13 0.048 0.005 No significant differences between regions14 0.000 0.000 Significant differences: NE and NW, T17 0.002 0.004 Significant differences: NW and T40 0.004 0.008 Significant differences: A and W

* Regions are abbreviated as follows: A = Anglian; M = Midlands; NE = North East; NW = NorthWest; S = Southern; SW = South West; T = Thames; W = Wales

3.1.4 Moving average trends for each region

The monthly temperature data have been plotted for all the sites on the selected main river foreach region. It should be noted that on some rivers such as the Thames it was not possible toplot all the sites due to the large number of available records; therefore, only sites with thelongest and most complete records have been plotted. The annual temperature cycle is clearlyevident in all the plots. The 12-month moving average of temperature has also been included (i.e.the mean of the previous 12 months' temperature data) to smooth out short-term fluctuations andhighlight longer term trends. The data have been plotted in 'stream order' with the most upstreamsite first and the most downstream site last. For each river the years with the highest and lowesttemperatures are noted and referred to as the warmest/hottest and coldest.


River Stour (Anglian Region) Temperature Plots with Moving Averages for Upper, Middle and Lower Reaches

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Figure 3.1 Anglian Region – River Stour moving average plots – upper, middle and lowerreaches

Figure 3.1 illustrates the monthly temperature data for all sites on the Stour. The coldest yearswere 1986 and 1991 and the hottest years were 1994, 1995 and 2005. Records were availablefrom 1981 to 2005, although the early period of the temperature record at the Great Bradley sitehas a significant amount of missing data. For the upper reach site (Great Bradley) temperaturesappear to have remained steady from 1989 onwards. For both the middle reach site (Liston Weir)and lower reach site (Cattawade) there has been a gradual rise in temperature of 1–2°C betweenthe early 1980s and 2005.

Figure 3.2 shows the monthly temperature data and moving average plots for the Ouse inAnglian Region. For this river the upper and middle reach sites (Brackley and Olney Weir) showa slight increase in temperature of approximately 1°C between the early 1980s and 2005,whereas at the lower reach site (Offord) there does not appear to be any overall change intemperature. At Brackley in particular, there is a distinct rise in temperature of approximately 5°Cbetween 1990 and 2001.


River Ouse (Anglian Region) Temperature Plots with Moving Averages for Upper, Middle and Lower Reaches

0

2

4

6

8

10

12

14

16

18

20

Jan-

81

Jan-

82

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83

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84

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85

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86

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87

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88

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90

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95

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99

Jan-

00

Jan-

01

Jan-

02

Jan-

03

Jan-

04

Jan-

05

Tem

pera

ture

in C

elsi

us

Offord 12 per. Mov. Avg. (Offord) 12 per. Mov. Avg. (Olney Weir) 12 per. Mov. Avg. (Brackley)

Figure 3.2 Anglian Region – River Ouse moving average plots – upper, middle and lowerreaches

The River Severn moving average plots are shown in Figure 3.3. The upper reach site(Llandrinio) shows a slight overall decrease in temperature between 1987 and 2005. In themiddle reach the site at Dolwen shows no change in temperature for the historical period, whileBewdley shows an upward temperature trend of approximately 1°C. The lower reach site atMythe also shows an upward trend. The coldest years were 1997 and 2002 and the warmestyears were 1995, 2003 and 2005.

Temperature data for the River Tyne in North East Region are shown in Figure 3.4. The upperreach site at Kielder shows no change in temperature for the period of the record (1973 to 2005),whereas both the middle and lower reach sites show a slight increase in temperature(approximately 1°C). The moving average trendlines show that the lower reach site (WylamBridge) is generally the warmest site and the upper reach site is generally the coolest. In theearly part of the record during the years 1975, 1977, 1978, 1980 and 1982, temperatures wereclose to zero during the winter at a number of sites. In later years, temperatures are close to zeroat just one site in 1999. The hottest years of the record are 1975, 1995 and 2005.

Figure 3.5 illustrates the monthly temperature data for the River Ribble in North West Region.Records were available from 1971 to 2005. In the early years (1975 to 1990) temperatures in theupper and middle reach sites are very similar, whereas from 1990 to 2002 and in 2005 the upperreach site (Settle Weir) is cooler than the middle reach site (Sawley Bridge). The lower reach site(Samlesbury) shows a slight increase (approximately 1°C) in temperature over the historicalrecord


River Severn (Midlands Region) Temperature Plots with Moving Averages for Upper, Middle and Lower Reaches

0

2

4

6

8

10

12

14

16

18

20

Jan-87

Jan-88

Jan-89

Jan-90

Jan-91

Jan-92

Jan-93

Jan-94

Jan-95

Jan-96

Jan-97

Jan-98

Jan-99

Jan-00

Jan-01

Jan-02

Jan-03

Jan-04

Jan-05

Tem

pera

ture

in C

elsi

us

12 per. Mov. Avg. (Llandrinio) 12 per. Mov. Avg. (Dolwen) 12 per. Mov. Avg. (Bewdley) 12 per. Mov. Avg. (Mythe W TW)

Figure 3.3 Midlands Region – River Severn moving average plots – upper, middle andlower reaches

River Tyne (North East region) Temperature Plots with Moving Averages for Upper, Middle and Lower Reaches

0

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6

8

10

12

14

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18

20

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73

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74

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75

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78

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79

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80

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81

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82

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84

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85

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86

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87

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88

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89

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90

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91

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92

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93

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94

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95

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96

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97

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98

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99

Jan-

00

Jan-

01

Jan-

02

Jan-

03

Jan-

04

Jan-

05

Tem

pera

ture

in C

elsi

us

12 per. Mov. Avg. (Kielder) 12 per. Mov. Avg. (Chollerford) 12 per. Mov. Avg. (Wylam Bridge)

Figure 3.4 North East Region – River Tyne moving average plots – upper, middle andlower reaches


River Ribble (North West Region) Temperature Plots with Moving Averages for Upper, Middle and Lower Reaches

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6

8

10

12

14

16

18

20

Jan-

71

Jan-

72

Jan-

73

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74

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75

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76

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77

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78

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79

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80

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81

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82

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83

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84

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85

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86

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87

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88

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90

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91

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92

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93

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94

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95

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96

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97

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98

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99

Jan-

00

Jan-

01

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02

Jan-

03

Jan-

04

Jan-

05

Tem

pera

ture

in D

egre

es C

elsi

us

12 per. Mov. Avg. (Sawley Bridge) 12 per. Mov. Avg. (Samlesbury) 12 per. Mov. Avg. (Settle Weir)

Figure 3.5 North West Region – River Ribble moving average plots – upper, middle andlower reaches

River Test (Southern Region) Temperature Plots with Moving Averages for Upper, Middle and Lower Reaches

0

2

4

6

8

10

12

14

16

18

20

Jan-78

Jan-79

Jan-80

Jan-81

Jan-82

Jan-83

Jan-84

Jan-85

Jan-86

Jan-87

Jan-88

Jan-89

Jan-90

Jan-91

Jan-92

Jan-93

Jan-94

Jan-95

Jan-96

Jan-97

Jan-98

Jan-99

Jan-00

Jan-01

Jan-02

Jan-03

Jan-04

Jan-05

Tem

pera

ture

in D

egre

es C

elsi

us

12 per. Mov. Avg. (Polhampton) 12 per. Mov. Avg. (Leckford) 12 per. Mov. Avg. (Testwood)

Figure 3.6 Southern Region – River Test moving average plots – upper, middle and lowerreaches


Figure 3.6 shows the temperature data for the River Test in Southern Region. The temperaturerecord runs from 1978 to 2005. The upper reach site (Polhampton) shows an overall slightdecrease in temperature for this historical period, the middle reach site (Leckford) indicates thatthe temperature does not change over the period of the record, and the lower reach site(Testwood) shows a very small increase in temperature. The lower reach site is generally thewarmest site and the upper reach site is the coolest. The coldest years are 1982 and 1986 andthe warmest years are 1981, 1987, 1995 and 2005.

The Tamar temperature data are shown in Figure 3.7. All the representative reach sites show anoverall increase in temperature of 1–2°C from 1974 to 2005. The coldest years are 1986, 1992and 2000 and the hottest years are 1994, 1995, 1996, 1997 and 2003. The middle and lowerreach sites (Boyton Bridge and Gunnislake Bridge, respectively) generally have a very similartemperature pattern except for 1984, 1988 and 1989 where missing data have resulted inrelatively higher or lower temperatures for the 12-month moving average calculations.

For the River Thames (Thames Region), all the representative reach sites show an overallincrease in temperature of 1–2°C between 1972 and 2005 (see Figure 3.8). Temperatures arelowest in the uppermost reach (Aston Keynes) and highest in the lowermost reach (Teddington).The coldest years are 1985, 1986 and 1997 and the hottest years are 1983, 1989, 1995 and2003. For the early part of the record (1973 to 1988) the temperature profile is similar at Day'sWeir, Teddington, Caversham and Egham. After 1988 the temperature profile at Eghambecomes much more variable and Caversham becomes relatively cooler than the other sites.Temperatures at Buscot are lower than the other middle reach sites between 1981 and 1991 andbetween 1999 and 2001.

Finally, the moving average plots for the River Dee (Wales Region) are illustrated in Figure 3.9. Alinear trendline shows that all three reaches increase in temperature by 1–2°C between 1974 and2005. The coldest years are 1984, 1985 and 1996, and the warmest years are 2001, 2002, 2003and 2005. The representative site for the upper reach (Llandderfel Bridge) is consistently coolerthan the lower reach site (Iron Bridge) except in 2001, where missing data in the Iron Bridge timeseries causes an apparent drop in the moving average trendline. The temperature series for themiddle reach (Overton Bridge) is variable, being warmer than the lower reach site in 1977, 1978,1987 to 1991, 1997 and 2001, and cooler than the lower reach in the remaining years.Newbridge is warmer than the upper reach site except in 1991 and 1992, when missing data inthe time series may again be altering the trendline.


River Tamar (Southwest Region) Temperature Plots with Moving Averages for Upper, Middle and Lower Reaches

0

2

4

6

8

10

12

14

16

18

20

Jan-

74

Jan-

75

Jan-

76

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77

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78

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79

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80

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81

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82

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83

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84

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85

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86

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87

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88

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89

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90

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94

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95

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96

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97

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98

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99

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00

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01

Jan-

02

Jan-

03

Jan-

04

Jan-

05

Tem

pera

ture

in D

egre

ss C

elsi

us

12 per. Mov. Avg. (Buses Bridge) 12 per. Mov. Avg. (Boyton Bridge) 12 per. Mov. Avg. (Gunnislake Bridge )

Figure 3.7 South West Region – River Tamar moving average plots – upper, middle andlower reaches

River Thames (Thames Region) Temperature Plots with Moving Averages for Upper, Middle and Lower Reaches

0

2

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6

8

10

12

14

16

18

20

Jan-72

Jan-73

Jan-74

Jan-75

Jan-76

Jan-77

Jan-78

Jan-79

Jan-80

Jan-81

Jan-82

Jan-83

Jan-84

Jan-85

Jan-86

Jan-87

Jan-88

Jan-89

Jan-90

Jan-91

Jan-92

Jan-93

Jan-94

Jan-95

Jan-96

Jan-97

Jan-98

Jan-99

Jan-00

Jan-01

Jan-02

Jan-03

Jan-04

Jan-05

Tem

pera

ture

in C

entig

rade

12 per. Mov. Avg. (Buscot) 12 per. Mov. Avg. (Egham) 12 per. Mov. Avg. (Caversham W eir)12 per. Mov. Avg. (Days Weir) 12 per. Mov. Avg. (Teddington) 12 per. Mov. Avg. (Aston Keynes)

Figure 3.8 Thames Region – River Thames moving average plots – upper, middle andlower reaches


River Dee (Welsh Region) Temperature Plots with Moving Averages for Upper, Middle and Lower Reaches

0

2

4

6

8

10

12

14

16

18

20

Jan-

74

Jan-

75

Jan-

76

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77

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78

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79

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80

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81

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82

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83

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84

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85

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86

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87

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88

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89

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90

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91

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93

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94

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95

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96

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97

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98

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99

Jan-

00

Jan-

01

Jan-

02

Jan-

03

Jan-

04

Jan-

05

Tem

pera

ture

in C

entig

rade

12 per. Mov. Avg. (Llandderfel Bridge) 12 per. Mov. Avg. (Iron Bridge) 12 per. Mov. Avg. (Overton Bridge)

Figure 3.9 Wales Region – River Dee moving average plots – upper, middle and lowerreaches

3.1.5 Annual mean and decadal trend analysis

Figure 3.10 shows the annual mean temperature trend for the best water temperature record ineach Environment Agency region, with standard error plots for each site in Figure 3.11. Details ofeach of the benchmark temperature monitoring sites are provided in Table 3.3. A summary of therate of annual mean river water temperature change (°C per decade) is given for each site inTable 3.4, with these results also being represented graphically in Figures 3.12 to 3.14.


Table 3.3 Benchmark site information

Site name Region NGR WFDtype

Recordstart date

Recordend date

Averagesamplingfrequency(days)

R StourWixoeWQMSintake pier

Anglian TL7083643102

5 30/03/1981 15/12/2005 6.25

Severn atSaxonsLode

Midlands SO8633039050

8 01/06/1975 31/10/2006 1.02

River HullatHempholme Lock

NorthEast

TA0798449885

5 01/04/1974 24/11/2005 5.17

RiverCalder atWhalley

NorthWest

SD7292736058

14 30/04/1971 15/12/2005 7.12

RiverCuckmereShermanBridge

Southern

TQ5320005050

5 07/01/1976 30/11/2005 11.20

RiverTamar atGunnislakeBridge

SouthWest

SX4349372436

4 03/04/1974 15/12/2005 8.88

Thames atCavershamWeir

Thames SU7213574053

8 05/01/1972 09/12/2005 4.17

River Deeat IronBridge

Wales SJ4180060100

17 09/04/1974 29/11/2005 12.56


0

2

4

6

8

10

12

14

16

18

20

19 70 1 975 1980 198 5 1 990 1995 20 00 2 005

Y ear

Ann

ual m

ean

tem

pera

ture

(deg

rees

C)

S ou thern annua l m eanS ou th W es t annua l meanT hame s annua l m eanW a les annua l m ean

0

2

4

6

8

10

12

14

16

18

20

19 70 197 5 1980 19 85 199 0 1995 2 000 200 5

Y ear

Ann

ual m

ean

tem

pera

ture

(deg

rees

C)

A n glian an nua l mea nM id la nd s a nnu a l me an

N orth E as t an nua l m ea nN orth W est an nu a l m e an

Figure 3.10 Annual mean water temperature trends for benchmark sites

Scie

nce

Rep

ort C

limat

e ch

ange

impa

cts

and

wat

er te

mpe

ratu

re38

Stou

r at W

ixoe

(Ang

lian

Reg

ion)

Sta

ndar

d Er

ror P

lot

051015202530

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Year

SEM (temperature degrees C)

Mea

n +

1 S

EMM

ean

- 1 S

EMM

ean

Seve

rn a

t Sax

ons

Lode

(Mid

land

s R

egio

n) S

tand

ard

Erro

r Plo

t

051015202530

1975

1976 1977

1978

1979

1980 1981

1982

1983 1984 1985

1986

1987 1988

1989

1990

1991 1992

1993

1994

1995 1996

1997

1998

1999 2000

2001

2002

2003 2004

2005

2006

Year


Mea

n +

1 SE

MM

ean

- 1 S

EMM

ean

Hul

l at H

emph

olm

e Lo

ck (N

orth

Eas

t Reg

ion)

Sta

ndar

d Er

ror P

lot

051015202530

1974

1975 1976

1977

1978

1979 1980

1981

1982 1983 1984

1985

1986 1987

1988

1989

1990 1991

1992

1993

1994 1995

1996

1997

1998 1999

2000

2001

2002 2003

2004

2005

Year


Mea

n +

1 S

EMM

ean

- 1 S

EMM

ean

Cal

der a

t Wha

lley

(Nor

th W

est R

egio

n) S

tand

ard

Erro

r Pl

ot

051015202530

1971

1973

1975

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

Year


Mea

n +

1 SE

MM

ean

- 1 S

EMM

ean

Scie

nce

Rep

ort C

limat

e ch

ange

impa

cts

and

wat

er te

mpe

ratu

re39

Cuck

mer

e at

She

rman

's B

ridge

(Sou

ther

n R

egio

n) S

tand

ard

Erro

r Plo

t

051015202530

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Year


Mea

n +

1 SE

MM

ean

- 1 S

EM

Mea

n

Tam

ar a

t Gun

nisl

ake

(Sou

th W

est R

egio

n) S

tand

ard

Erro

r Plo

t

051015202530

1974

1975 1976

1977

1978

1979 1980

1981

1982 1983 1984

1985

1986 1987

1988

1989

1990 1991

1992

1993

1994 1995

1996

1997

1998 1999

2000

2001

2002 2003

2004

2005

Year


Mea

n +

1 SE

MM

ean

- 1 S

EM

Mea

n

Tham

es a

t Cav

ersh

am (T

ham

es R

egio

n) S

tand

ard

Erro

r Pl

ot

051015202530

1972

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

19901991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Year


Mea

n +

1 S

EMM

ean

- 1 S

EMM

ean

Dee

at I

ron

Brid

ge (W

ales

Reg

ion)

Sta

ndar

d Er

ror P

lot

051015202530

1974

1975 1976

1977

1978

1979 1980

1981

1982 1983 1984

1985

1986 1987

1988

1989

1990 1991

1992

1993

1994 1995

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1997

1998 1999

2000

2001

2002 2003

2004

2005

Year


Mea

n +

1 SE

MM

ean

- 1 S

EM

Mea

n

Figu

re 3

.11

Stan

dard

err

or p

lots

for b

ench

mar

k si

te a

nnua

l tem

pera

ture

tren

ds


Table 3.4 Rate of decadal temperature change

Site name Temperaturechange 1970–1980(°C)

Temperature change1980–1990 (°C)

Temperaturechange 1990–2000 (°C)

River Stour WixoeWQMS intake pier

No data 1.10 -0.06

Severn at SaxonsLode

0.02 0.15 0.78

River Hull atHempholme Lock

-0.14 0.46 0.23

River Calder atWhalley

-1.02 0.89 0.01

River CuckmereSherman Bridge

0.11 0.26 0.28

River Tamar atGunnislake Bridge

-0.36 0.10 0.36

Thames atCaversham Weir

1.41 -0.36 0.07

River Dee at IronBridge

-0.64 1.04 -0.25

Air temperatures(HadCET)

-0.02 0.58 0.34

Figure 3.12 Decadal temperature change at benchmark sites, 1970-1980

-1 .5

-1

-0.5

0

0.5

1

1.5

2

Temperature monitoring site

Tem

pera

ture

cha

nge

(deg

rees

C)

HadCET dataSevern at Saxon's LodeHull at Hempholme LockCalder at WhalleyCuckmere at Sherman BridgeTamar at GunnislakeThames at CavershamDee at Iron Bridge


-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2


Tem

pera

ture

cha

nge

(deg

rees

C)

HadCET dataStour at WixoeSevern at Saxon's LodeHull at Hempholme LockCalder at WhalleyCuckmere at Sherman BridgeTamar at GunnislakeThames at CavershamDee at Iron Bridge

Figure 3.13 Decadal temperature change at benchmark sites, 1980–1990

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1


Tem

pera

ture

cha

nge

(deg

rees

C)

HadCET dataStour at WixoeSevern at Saxon's LodeHull at Hempholme LockCalder at WhalleyCuckmere at Sherman BridgeTamar at GunnislakeThames at CavershamDee at Iron Bridge

Figure 3.14 Decadal temperature change at benchmark sites, 1990–2000


3.1.6 Seasonal analysis

The seasonal analysis uses January to March as winter, April to June as spring, July toSeptember as summer and October to December as winter (as requested by the EnvironmentAgency). Figures 3.15 to 3.18 show the 5-year moving averages for upper and lower reach siteson the main rivers selected for each region. The Aston Keynes site on the Thames has missingdata for 1984 to 1998, the River Stour at Great Bradley has missing data from 1984 to 1988, theHorton site on the River Ribble has missing data from 1984 to 1992 and the Tyne has missingdata from 1988 to 1989. This missing data causes anomalous peaks and troughs in the movingaverage data.

Figure 3.15 indicates that all the upper reach sites show a similar trend in winter except for theStour site, which is likely to be affected by transfers from the Ouse catchment, and the Tyne site,which may be affected by Kielder reservoir. Both the Stour and Tyne sites show a slightdownward temperature trend whereas all the other sites show an upward trend.

Figure 3.16 indicates that all the lower reach sites show an upward temperature trend in winter.The Stour site (Cattawade) experienced particularly high temperatures during the early years(1980 to 1988) and the Tyne site (Wylam Bridge) experienced high temperatures between 1985and 1991.

0

2

4

6

8

10

12

1970

1971

1972

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Mea

n S

easo

n Te

mpe

ratu

re in

Deg

rees

Cen

tigra

de

5 per. Mov. Avg. (Stour @ Great Bradley) 5 per. Mov. Avg. (Ouse @ Brackley) 5 per. Mov. Avg. (Dee @ Llandderfel Bridge)5 per. Mov. Avg. (Ribble @ Horton) 5 per. Mov. Avg. (Severn @ Dolwen) 5 per. Mov. Avg. (Tamar @ Buses Bridge)5 per. Mov. Avg. (Thames @ Aston Keynes) 5 per. Mov. Avg. (Tyne @ Kielder) 5 per. Mov. Avg. (Test @ Polhampton)

Figure 3.15 Upper reach sites winter 5-year moving average trends


0

2

4

6

8

10

12

1970

1971

1972

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Mea

n S

easo

n Te

mpe

ratu

re in

Deg

rees

Cen

tigra

de

5 per. Mov. Avg. (Stour @ Cattawade) 5 per. Mov. Avg. (Ouse @ Offord) 5 per. Mov. Avg. (Dee @ Iron Bridge)

5 per. Mov. Avg. (Ribble @ Sawley Bridge) 5 per. Mov. Avg. (Severn @Westgate Bridge) 5 per. Mov. Avg. (Tamar @ Gunnislake Bridge )

5 per. Mov. Avg. (Thames @ Teddington) 5 per. Mov. Avg. (Tyne @W ylam Bridge) 5 per. Mov. Avg. (Test @ Testwood)

Figure 3.16 Lower reach sites winter 5-year moving average trends

The upper reach spring temperatures shown in Figure 3.17 again illustrate a general upwardtrend in water temperatures, although the Rivers Ribble and Stour show a slight downward trend.

The lower reach spring temperatures in Figure 3.18 also show a general upward trend over timeexcept for the Ribble, Tamar and Ouse. The River Ribble in particular shows a dip intemperatures between 2000 and 2003.

Overall, the water temperature of rivers in northern England such as the Tyne (North EastRegion) are cooler than rivers in southeast England such as the Thames (Thames Region) andthe Ouse (Anglian Region).


0

2

4

6

8

10

12

14

16

1819

70

1971

1972

1973

1974

1975

1976

1977

1978

1979

1980

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Figure 3.17 Upper reach sites spring 5-year moving average trends

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Figure 3.18 Lower reach sites spring 5-year moving average trends

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Figure 3.19 shows the seasonal temperature curves for individual upper reach sites. Asexpected, temperatures are lowest in winter and highest in summer. For the Ouse at Brackleythere is some overlap between the winter and spring temperatures in 1989, 1990 and 1999. Forthe Tyne at Kielder there is overlap between autumn and spring temperatures between 1976 and1987 and unusually warm winter temperatures in 1984 and 1987. This could be due to erroneousdata or the effects of Kielder reservoir. The River Test at Polhampton shows an overlap in winterand spring temperatures in 1982 and 1990. The Rivers Tyne and Ribble have lower wintertemperatures than rivers in the more southern regions.

The seasonal plots for the lower reach sites are shown on Figure 3.20. Again, rivers in the NorthEast and North West Regions have the lowest winter temperatures. Winter and springtemperatures for the River Tyne at Wylam Bridge overlap in 1986 to 1988 and 1998 and springand summer temperatures overlap in 1987, 1988 and 2001.

3.2 Analysis of daily data


Daily data were obtained for four regions: Midlands, North East, Thames and Wales. ANOVArevealed significant differences in water temperature between all four regions and combinationsof regions (p < 0.01). The highest mean water temperature was recorded in Thames Region(12.24°C) and the lowest in Wales (10.08°C).

3.3 Infilling water temperature time seriesTable 3.5 shows the results from regression analysis between sites of the same typology fromdifferent regions. The regression was carried out to ascertain the feasibility of infilling and/orhindcasting temperature time series data using a donor site of the same type from anotherregion. The table illustrates that the R-squared values (the amount of explained variance) fromthe regression analysis are high, ranging from 0.83 to 0.88. It should be noted that infilling canonly be successfully accomplished by using near-neighbour donor sites. It is not appropriate touse a donor site in Southern Region to infill temperature data for a river in North West Region forexample.

Figures 3.21 and 3.22 show the regression analysis of WFD Type 13 rivers at sites in the NorthEast and North West Regions regressed against the Churnet and Derwent in the MidlandsRegion. Figures 3.23 and 3.24 show the regression for WFD Type 8 rivers at sites on the RiverThames regressed against sites on the River Severn in Midlands Region.


Table 3.5 Regression analysis results

Donor site Infill site Regression equation R-squaredThames Type 8 Midlands Type 8Thames at Buscot Severn at Haw Bridge y = 0.9969x + 0.1850 0.83Thames at Abingdon Severn at Haw Bridge y = 0.9176x + 0.5918 0.88Thames at Buscot Severn at Tewkesbury y = 1.0528x – 0.8136 0.85Thames at Abingdon Severn at Tewkesbury y = 0.9481x – 0.0943 0.88North East Type 13 Midlands Type 13Wharf at Tadcaster Churnet at Cheddleton Y = 0.8121x + 1.6165 0.85Wharf at Tadcaster Derwent at Little Eaton Y = 0.7843x + 2.0885 0.85North West Type 13 Midlands Type 13Irwell at Wark Weir Churnet at Cheddleton Y = 0.8544x + 1.4461 0.86Irwell at Wark Weir Derwent at Little Eaton Y = 0.8377x + 1.7909 0.84

y = 0.7843x + 2.0885R2 = 0.853

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Figure 3.22 Regression analysis of River Irwell at Wark Weir (Type 13 North WestRegion) versus River Churnet at Cheddleton Station (Type 13 Midlands Region)

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Figure 3.24 Regression analysis of River Thames at Abingdon (Type 8 Thames Region)versus River Severn at Haw Bridge (Type 8 Midlands Region)

3.4 Air temperature dataThe Hadley Centre Central England Temperature (HadCET) dataset is already in the publicdomain, and holds monthly mean temperatures from 1659 and daily temperatures from 1772(Parker et al. 1992). The HadCET area is roughly representative of a triangle enclosed by Bristol,Lancashire and London. Daily and monthly maximum and minimum temperatures have beencalculated for the period beginning 1878 and monthly and annual gridded 5 x 5 km temperaturedatasets for the period 1961–2000 are freely available from the Met Office for research purposes.Information on the available data can be found on the Met Office website.

If additional MORECS data are required, costs for a licence have been quoted by the Met Officeto be £5936.00 + VAT for weekly maximum and minimum temperatures covering all of Englandand Wales (130 squares) for the entire record available (1961–2006). Data for a shorter timeperiod are also available at a reduced cost of £5147.00 + VAT for 1970–2006 and £3967.00 +VAT for 1980–2006. This licence is for a period of 5 years only and is subject to Met OfficeTerms and Conditions. Data should be delivered within 10 days of a request.

At a cost, the Met Office will also give consultancy advice on obtaining the most relevant data fora particular project if detailed information is provided on the aims and objectives.


4 Analysis and discussion

4.1 Analysis of monthly data


Significant regional differences in river water temperature have been identified, with the highestvalues being recorded in the Thames (River Thames) and Anglian Regions (Rivers Stour andOuse) and the lowest in the North East Region (River Tyne). While ANOVA revealed there to besignificant differences in water temperature between most combinations of regions (Section3.1.1), no significant differences were found between Anglian and Thames Regions, Midlandsand Southern Regions, Midlands and South West Regions, Midlands and Wales Regions, andSouthern and South West Regions. This result is not unexpected, with the more southerlyregions (Anglian and Thames, Southern and South West) being more similar to each other interms of water temperature than the northern regions (Midlands and Wales, North East and NorthWest) and vice versa. The similarity between Midlands and Southern Regions, and Midlands andSouth West Regions, however, is surprising and not easily explained.

4.1.2 Type analysis within regions

River typology appears to have a significant effect on river water temperatures within regions,with ANOVA revealing significant differences in water temperature between river types for allregions apart from Anglian Region. This anomaly may be explained by lack of topographic rangeof the Anglian rivers, to the lack of rainfall and to the significant management of the Anglian riversused in the analysis.In contrast within Welsh Region for example, the water temperature of Type1 (low altitude, siliceous geology, small catchment size) rivers is different from that of Type 11(mid altitude, calcareous, small catchment size) and Type 13 (mid altitude, siliceous, mediumcatchment size) rivers, but similar to all other types present in the region. As typology is derivedfrom the combination of catchment altitude, geology and size, it is probably a combination ofthese factors that influences water temperature – no single factor has been identified as themajor influence. For example, it is well known that the temperature regime of groundwater-fedchalk streams is relatively stable compared with that of clay or limestone rivers that receive lesssignificant groundwater inputs (Mackey and Berrie 1991). Similarly, a large river will be lesssensitive to air temperature fluctuations than a small headwater stream (Caissie et al. 1998).

As each region contained a different number and range of river types, meaningful comparisonscannot be made regarding which types differ most often within regions in terms of watertemperature. In particular, high altitude sites were not well represented in the datasets collectedand cannot be included in the conclusions. It is interesting to note that within Anglian Regionthere are apparently no differences in river water temperature related to type. All of the rivertypes included in the Anglian analysis were classed as low altitude, whereas all possiblegeologies and sizes were covered. This might be the cause of the lack of differences in watertemperature. However, similar types were included within the Thames Region analysis, which didshow differences in water temperature related to type and between types of the same altitude.More detailed statistical analysis of the existing water temperature data stratified by catchmentaltitude, geology and size is required to further investigate the causes of the temperaturedifferences.


4.1.3 Type analysis between regions

Statistical analysis revealed that the water temperature of all river types included in the analysisdiffers between regions. For example, the water temperature of a Type 2 river in Anglian Regionis not the same as the water temperature of a Type 2 river in North East, North West, Southern,South West and Thames regions. Therefore, the effect of region on river water temperaturerevealed by the regional analysis appears to be stronger in some cases than the effects of rivertype (catchment altitude, geology and size).

As not all types were present in all regions, the number of regions compared for each type wasnot equal and conclusions cannot therefore be made regarding which types differ more oftenbetween regions in terms of water temperature. In particular, there was a lack of upland riversites suitable for inclusion in the analysis.

4.1.4 Moving average trends for each region

An upward trend in mean annual river water temperatures over the period of the temperaturerecord was identified in all regions. In particular, all reaches of the River Thames (ThamesRegion) and River Tamar (South West Region) and most reaches in Anglian Region (RiversOuse and Stour) showed an increase in water temperature with time. The highest temperatureswere more likely to be seen after 1990 and the coldest temperatures in the earlier part of therecord (1970s and 1980s). Within rivers in the more northern regions such as the North East andNorth West Regions (Rivers Tyne and Ribble, respectively), the warming trend was less apparentand often seen only in the middle and lower reaches of the river. However, all rivers showedsome evidence of a warming trend in the lower reaches, and the warmest years were again seenin the later part of the record. This confirms that river water temperatures are rising across theUK and suggests that such increases are likely to occur more often (but not exclusively) in thesouth and east of the country, and in the middle and lower reaches of the river.

4.1.5 Annual mean and decadal trend analysis

The trend in annual mean water temperatures for the benchmark site in each region (Figure 3.10)spans approximately 35 years (1970 to 2005). A temperature record of at least 100 years isideally required to identify any warming trends that have occurred during the last century.However, a slight warming trend since approximately 1980 can be seen in nearly all regions,although this follows an apparent dip in annual mean temperatures during the 1970s. Annualmean temperatures from regions in the south and east of the country (e.g. Southern, Thames)tend to be higher than those in the north (e.g. North East). Mean annual temperatures in Walesand the North West are generally lower than other regions. The annual mean in Wales wasnotably lower in 1983 (along with that of North East Region) and 2001 when Southern Regionand Anglian also exhibited significant lower annual means. It should be noted that the selectionof only one benchmark site from each region might be misleading if the chosen site is notrepresentative of the region as a whole (e.g. if artificial influences are affecting a site).

Figure 3.11 shows the mean annual temperature trend for each benchmark site individually, withthe standard error of the mean (SEM) also plotted. This represents the standard deviation of thedifferent sample means and tends to increase as the variability of the data increases anddecrease as sample size increases. There is a general trend in the benchmark sites of the SEMto increase noticeably over the last 5 or 6 years of the record (since approximately 2000),particularly in Anglian, Southern and North West Regions. This might be a result of an increasein maximum water temperatures since this time, as confirmed by the slight warming trendidentified in Figure 3.10.


The decadal trends in water temperature are shown in Figures 3.12 to 3.14 and Table 3.4.Between 1970 and 1980, the mean annual water temperature at most of the benchmark sitesdecreased, except in the Southern and Thames Regions. Between 1980 and 1990, and 1990and 2000, mean annual water temperatures tended to increase, particularly between 1980 and1990 (with the exception of the Thames at Caversham, which showed a slight decrease). Itshould be noted in Figure 3.14 that for two sites, the Dee in Welsh Region and the Stour inAnglian Region, the decadal water temperature is lower. No one region experienced consistentlymore rapid changes in water temperature than the others. The HadCET air temperature datasetshows a similar decadal pattern, suggesting that changes in river water temperature arecomparable to changes in air temperature over a time period of several years.

4.1.6 Seasonal analysis

For the upper reach sites in Winter the River Test is significantly warmer, by 1 to 4 degrees, thanthe other rivers with the Tamar and Ouse generally being the next warmest. The River Tyne isgenerally colder, with the anomalies in 1988, 1989 and 1991 being due to missing data. For thelower reaches in winter the Rivers Test, Tamar and Thames have the highest temperatures fromthe late 1980s onwards. Prior to this the River Thames is significantly lower. The Rivers Ribbleand Tyne have the lowest temperatures. The River Tyne has missing data in 1989.

Figures 3.17 and 3.18 show the upper and lower sites in spring. For the upper sites AstonKeynes has missing data from 1983 to 1998 and the Tyne has missing data in 1988 and 1989.The Tamar and Tyne are the coolest from the 1970s till the mid 1990s, after which it is the Tyneand Ribble which are the coolest till 2000, with the Severn and Ribble being the coldest from2000 onwards. For the lower sites in spring the warmest rivers are the Stour, Thames and Ousewith these three rivers being noticeably warmer from the 1990s onwards with a pronouncedupward trend. The coldest rivers are Tyne and Dee up until the 1990s, after which it is the Ribbleand Tyne which are the coolest until 2000 when the Tyne becomes relatively warmer than theTest.

For the upper and lower reach comparisons on the Ouse, winter water temperatures are slightlyhigher for the upper reach site whereas spring and summer temperatures are higher for the lowerreach site. Winter and autumn temperatures in the River Dee are very similar for both the upperand lower reach sites, but spring and summer water temperatures are higher at the lower reachsites. When comparing the lower and upper reach sites of the Ribble, the seasonal data are verysimilar from the 1970s through to the mid 1990s. From 1994 the spring and summertemperatures at the upper reach site are lower than those at the lower reach site.

For the Rivers Severn, Tyne and Tamar, winter and autumn temperatures are similar for theupper and lower reach sites whereas spring and summer temperatures are noticeably warmer atthe lower reach sites. On the River Thames during the 1970s and 1980s, water temperatures arelower at the upper reach sites in the summer but similar during winter, spring and autumn.However, from 2000 onwards autumn temperatures are lower for the upper reach site andsummer temperatures are 4 to 5 degrees lower at the upper reach site. The gradual rise in watertemperature from 1970 to 2005, particularly during spring and summer, is very clear in the RiverThames plot. For the River Test, winter temperatures are higher in the upper reach sites. Autumntemperatures for this river are similar at both sites and spring and summer temperatures areappreciably higher at the lower reach site.

For the individual river sites, as expected, the winter temperatures are generally the coolestfollowed by autumn and spring, with the summer being the warmest. Some inter-changeabilityoccurs between winter and autumn temperatures on the River Ouse at Brackley, the Test atPolhampton and the Tyne at Wylam Bridge. Assessing the higher temperatures, the Rivers Test


at Polhampton (upper reach) and Ribble at Sawley Bridge (lower reach) have overlap betweenthe spring and summer temperatures.

Analysing the lower reach sites the Rivers Tamar and Test have the least seasonal temperaturerange and the Ouse, Ribble and Severn have the greatest. Of the upper reach sites the RiverTest has the least seasonal range and the Rivers Tyne, Thames and Ribble have the greatestrange.

The moving average seasonal plots show a general upward trend in water temperature for bothwinter and spring. As expected, spring water temperatures are higher than winter watertemperatures and rivers in the south, southeast and southwest of England are warmer than thosein the northwest, northeast or Wales. Overall there appears to be evidence that the upperreaches (headwaters) are warming in winter and spring, whereas the lower reaches are warmingin summer.

4.2 Analysis of daily data


A strong effect of region on daily water temperatures was revealed by ANOVA, with significantdifferences between all four regions and combinations of regions included in the analysis(Midlands, North East, Thames and Wales). Therefore, river water temperature in MidlandsRegion is significantly different from river water temperature in North East Region, ThamesRegion and Wales; river water temperature in North East Region is significantly different fromriver water temperature in Midlands, Thames and Wales Regions and so on. Although watertemperatures in the adjacent Midlands and Wales Regions might be expected to be similar, theresults of the regional analysis are in overall support of the conclusions drawn from the monthlyregional analysis; regional differences in river water temperature exist and temperatures in thesouthern and eastern parts of the country tend to differ from temperatures in the north and west.However, a much larger dataset of daily water temperature data from all eight regions is requiredbefore firm conclusions can be made.

4.3 Infilling water temperature time seriesThe R-squared results from the regression analysis suggest that there is a reasonable correlationin water temperature between sites of the same typology from different regions. However, itshould be noted that this is not always the case, as demonstrated by the statistical analysis inSection 3.1.3. A good correlation in water temperature between two sites would allow infilling ofmissing data and the hindcasting of temperature data to simulate a water temperature timeseries. It is suggested that this type of regression can only be carried out for sites in adjoiningregions and ideally those which are geographically close, although again it should be noted thatwater temperatures in adjoining regions will not necessarily be similar (see Section 3.1.1). It isalso recommended that only sites of the same typology are included in this analysis.

4.4 Costs of external datasetsMany water temperature datasets held by external organisations were not freely available to theEnvironment Agency. The costs associated with obtaining such datasets varies according to thedatabase size, ease of access and the number and length of records requested. Often, thecharge is made for staff time to retrieve the records rather than for use of the data itself. Forexample, weekly river water temperature data are available from the ECN/CEH. Summary ECN


data are freely available on the website, but raw data are only made available to other users via alicensing system and with agreement from ECN sponsors. Only academic users can receive thedata free of charge while private requests attract a cost both from the sponsors and for CEH stafftime in extracting the data. These costs were estimated to be in the region of £150 to £500depending on the number and type of sites required, and at least 3 weeks is required to fulfil anydata requests. There is also an additional requirement for the agreement of the data owner in thecase of most datasets, such as datasets from the Lowland Catchment Research programme(LOCAR) and the Catchment Hydrology And Sustainable Management (CHASM) project.

The CEH was found to be the main source of water temperature data that is not freely availableand is known to hold some good long-term water temperature datasets that it would beappropriate to extract. Other organisations that will release water temperature data with a likelycost include the Freshwater Biological Association (FBA) at Windermere, and the UniversityCollege London Acid Waters Monitoring Network (lake data). Details of external datasets andassociated costs can be found in Appendix B.

In addition to the problem of costs, it is likely that data requests to external organisations will takeseveral weeks to be fulfilled.

4.5 Maintenance of the archiveMaintaining a national water temperature archive for the sites and rivers identified and includedin the analysis should be a relatively simple task. It would require time to be set aside to contactthe data owners for regular updates with the most recent data, ideally every 6 months. Themajority of the monthly sites are monitored by the Environment Agency and stored on the WIMSdatabase, requiring a simple update at no cost other than the time required. The daily data wereobtained from different sources within the Environment Agency and would require more time persite to contact the data owner and obtain the most recent monitoring data. However, there are arelatively small number of daily sites to be kept updated. Should any data in future be obtainedfrom external organisations, these would also need to be contacted for regular updates. It shouldbe considered that updates from external organisations might be associated with a financial cost.

4.6 Gap analysisDuring the course of the project, a number of gaps have been identified in terms of datarequirements and additional analyses. These are as follows:

1. Availability of good quality long-term temperature data (ideally, records spanning at least100 years). For example, Webb and Nobilis (2007) analysed water temperature datacollected from Austrian rivers over the period 1901 to 2001, allowing confidentidentification of a recent upward trend in river water temperatures. The longesttemperature records included in this study ran from the early 1970s to the end of 2005,although a few sites began in the 1960s (North West and South West Regions, Wales).

2. Frequency of monitoring. Ideally, temperature should be monitored daily, but at the veryleast monthly.

3. Data quality. Regardless of the length and monitoring frequency of the dataset, the qualityis extremely important. Most of the temperature records analysed in this project had gapsin the time series, with months during which no temperatures were recorded. In general, acomplete monthly temperature dataset would be preferable to a daily dataset with missingmonths or years.

4. River typology. In order to better analyse the effects of river type on water temperature,full water temperature records for every type present in every region are required. Thiswas not available for this study.


5. Lake temperature analysis. This project has already identified suitable lake watertemperature datasets. A similar analysis could therefore be undertaken for laketemperatures, and potentially extended to other waterbody types such as estuaries.

6. Air temperature analysis. Local air temperatures could be regressed against river watertemperatures to determine the relationship between the two. Air temperatures could thenbe used to hindcast water temperatures back in time before actual monitoring began, andalso to model future water temperatures under climate change scenarios. This approachis advantageous because long-term air temperature data are more easily available thanlong-term water temperature data. Assessment of river water temperature data againstlocal air temperature data for the same time period would be required for each site inorder to assess the need for incorporation of a time lag into any model.

7. Specific site details. The analysis carried out on the temperature data does not accountfor any anthropogenic effects on the river water temperatures. In order to assess theseeffects specific site details need to be collated, which was not part of the brief for thisproject.


5 ConclusionsMean river water temperature taken from a subset of rivers differs significantly betweenEnvironment Agency regions, with the largest difference of 2.5°C occurring between the Thamesand North East Regions. In particular, the highest mean monthly water temperatures were foundin the southeast of the UK (Anglian Region and Thames Region) and the lowest in the North EastRegion. Analysis of daily water temperatures shows the same trend, with significant temperaturedifferences existing between all four regions included in the analysis.

Within the same region, river water temperatures also differ according to the WFD river typology.This is probably related to factors such as the catchment geology, altitude and size. However,the water temperature of all the river types included in the analysis differs between regions,suggesting that the influence of region (geographic location) on river water temperature is oftenstronger than the influence of river type (catchment altitude, geology and size).

Moving average plots of water temperature data from the main river in each region have revealedan upward temperature trend over the last 20 to 30 years. This trend is particularly apparent inthe Anglian, Thames and South West Regions, but is also seen in the lower reaches of the mainriver analysed in all regions. In addition, moving average seasonal plots from each main riveridentified a general upward trend in water temperature in winter and spring. The plots confirmthat river water temperatures have increased in recent years, and suggest that the warming trendis likely to be more noticeable in the south and east of the UK and in the lower reaches of a river.It should however be noted that no uplands rivers were analysed as there was no temperaturedata available for these WFD river types.

Analysis of the mean annual and mean decadal water temperature trend for one benchmark sitein each region also provides evidence that water temperatures have increased in recentdecades, particularly since 1980. The decadal changes in river water temperature arecomparable to the changes in air temperature seen during the same period. However, since mostof the records analysed began in the 1970s or later, it was not possible to evaluate watertemperature trends before this time.

It is important to note that there is an overall lack of high-quality, complete, long-term watertemperature monitoring datasets, which has limited the analysis to some extent. Additional long-term water temperature data can be obtained from external organisations at a financial cost, butimproved Environment Agency water temperature monitoring would be preferred. The costs ofmaintaining and updating a water temperature database in the future should not be prohibitivelyhigh and are mostly in the form of the staff time required.

Infilling and hindcasting of temperature data is possible if sites are geographically close and ofthe same typology. The appropriateness of such a methodology would, however, need to betested for each donor and recipient site pairing to ensure that the resulting R-squared valuesfrom the regression analysis were high.

The river water temperature analysis carried out in this project could be built upon and extendedto other types of waterbody such as lakes and estuaries, as detailed in the Recommendations.


6 RecommendationsThe following recommendations can be made following the completion of this project:

1. Improve Environment Agency water temperature monitoring in terms of frequency,completeness of the time series and quality control. Consideration should also be given toequal representation of sites with regard to river type (catchment size, geology andaltitude). High altitude sites in particular are currently not represented. The assessment offuture indicator site monitoring requirements for river temperature data needs to be clearlyquantified and qualified as the initial step for the next phase of the climate change impacton river temperature programme, particularly in the light of local influences such assignificant abstractions and discharges.

2. Obtain urgently any relevant long-term water temperature datasets from externalorganisations such as CEH. This could be achieved by the establishment of anagreement with research councils and other organisations to share data for the use ofnon-profit-making projects and reports. Collate any further existing data which reportedlyexists, such as daily data for Anglian Region.

3. Maintain a water temperature archive to include regular updates of the best sitesidentified by this project (as a website or database). This will produce long-term watertemperature records for future analysis, and the costs and time required should berelatively small.

4. Undertake more detailed analysis of river water temperature in terms of seasonal trendsin warming, to determine whether warming is occurring at a greater rate in summer orwinter.

5. Complete the water temperature analysis for lakes using similar analysis techniques tothose used for rivers, although the amount of available lake temperature data is smaller.Follow up proposed co-ordination of results from LDMS.

6. Extend the project to cover estuarine and tidal sites.7. Further investigate the potential of air temperature analysis. Air temperatures could

potentially be used to hindcast river water temperatures to create a longer time series,and for modelling of future water temperatures under a climate change scenario. Themajority of the air temperature data required for such modelling is likely to be freelyavailable from the Met Office.

8. Specific details for each site need to be collated in order to identify any anthropogeniceffects on water temperatures.

9. Assess the effect of temperature changes on ecology. The effects of increased watertemperatures on ecology was not part of the current study, but would logically be part ofthe next phase of work. This would include links to growing seasons, thermal refugia andlethal thresholds.

10. Consideration of adaptive measures. If climate change is significantly affecting watertemperature, what can be done to reduce any detrimental effects? What are the costs andbenefits of such actions? The effects of land use on water temperature also need to beassessed.


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List of abbreviationsANOVA Analysis of VarianceCCC Canadian Center of Climate ModellingCCW Countryside Council for WalesCEH Centre for Ecology and HydrologyCHASM Catchment Hydrology And Sustainable ManagementECN Environmental Change NetworkFBA Freshwater Biological AssociationGCM General Circulation ModelHadCET Hadley Centre Central England Temperature datasetLDMS Lake Dynamics Monitoring StationsLOCAR Lowland Catchment Research programmeMORECS Meteorological Office Rainfall and Evaporation Calculation SystemNAO North Atlantic OscillationNERC Natural Environment Research CouncilSEM Standard Error of MeanSPSS Statistical Package for the Social SciencesTIMS Tideway Information Management SystemTukey's HSD Tukey's Honestly Significant Difference testWFD Water Framework DirectiveWIMS Water Information Management SystemWISKI Water Information Management System Kisters


Appendix APro forma for data collection

TEMPERATURE RECORD PRO FORMA

A. General informationRegion name River/lake name

Site name Grid reference

Contact details (name, phone, email)

B. Sample informationSampling frequency Length of record (dates)

Is the record continuous? If not, where do gaps of > 1 month exist?

Has any Quality Assurance been done?

Reason for data collection

Other data recorded at site

C. Data availabilityStorage medium (electronic/paper) and format. Please provide a sample if possible.

Storage location (central database, local hard drive etc)

Is the dataset easily accessible? If not, please indicate why.

Are the data in the public domain or is there a cost? Please indicate any likely costs

D. Information to be completed for lakes only

Sampling depth

Scie

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of r

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and

lake

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limat

e ch

ange

impa

cts

and

wat

er te

mpe

ratu

re71

Mid

land

s R

iver

Dat

a so

urce

Reg

ion

Site

nam

eG

rid re

fSa

mpl

ing

dept

h (m

)Sa

mpl

ing

freq

uenc

yLe

ngth

of r

ecor

dC

ontin

uous

reco

rd?

QA/

QC

Purp

ose

Stor

age

med

ium

Stor

age

loca

tion

Acce

ssib

ility

Cos

t

EA

Tw

erto

nM

idla

nds

3334

site

sIn

clud

edN

AV

arie

s19

87–2

005

Var

ies

Yes

– M

IDA

SM

ultip

leE

lect

roni

c –

Ora

cle

dow

nloa

ded

to u

sas

Acc

ess

Twer

ton

Goo

dN

one

EA

Mid

land

sS

ever

n –

Abe

rmul

eS

O16

4695

79N

AD

aily

mea

ns19

75–p

rese

ntN

o –

smal

l gap

sdu

e to

brea

kdow

n

Unk

now

nFi

sher

ies

Ele

ctro

nic

– E

xcel

Nat

iona

lFi

sher

ies

Tech

nica

l Tea

m

Goo

dN

one

EA

Mid

land

sS

ever

n –

Bew

dley

SO

7815

7622

NA

Dai

ly m

eans

1975

–pre

sent

No

– sm

all g

aps

due

tobr

eakd

own

Unk

now

nFi

sher

ies

Ele

ctro

nic

– E

xcel

Nat

iona

lFi

sher

ies

Tech

nica

l Tea

m

Goo

dN

one

EA

Mid

land

sTe

me

–B

rans

ford

SO

8038

5324

NA

Dai

ly m

eans

1975

–pre

sent

No

– sm

all g

aps

due

tobr

eakd

own

Unk

now

nFi

sher

ies

Ele

ctro

nic

– E

xcel

Nat

iona

lFi

sher

ies

Tech

nica

l Tea

m

Goo

dN

one

EA

Mid

land

sC

lyw

edog

–B

rynt

ail

SN

9136

8678

NA

Dai

ly m

eans

1989

–pre

sent

No

– sm

all g

aps

due

tobr

eakd

own

Unk

now

nFi

sher

ies

Ele

ctro

nic

– E

xcel

Nat

iona

lFi

sher

ies

Tech

nica

l Tea

m

Goo

dN

one

EA

Mid

land

sA

von

– E

vesh

amS

P04

0143

76N

AD

aily

mea

ns19

75–p

rese

ntN

o –

smal

l gap

sdu

e to

brea

kdow

n

Unk

now

nFi

sher

ies

Ele

ctro

nic

– E

xcel

Nat

iona

lFi

sher

ies

Tech

nica

l Tea

m

Goo

dN

one

EA

Mid

land

sV

yrnw

y –

Mei

fod

SJ1

5631

292

NA

Dai

ly m

eans

1975

–pre

sent

No

– sm

all g

aps

due

tobr

eakd

own

Unk

now

nFi

sher

ies

Ele

ctro

nic

– E

xcel

Nat

iona

lFi

sher

ies

Tech

nica

l Tea

m

Goo

dN

one

EA

Mid

land

sS

ever

n –

Mon

tford

SJ4

1191

445

NA

Dai

ly m

eans

1975

–200

2N

o –

smal

l gap

sdu

e to

brea

kdow

n

Unk

now

nFi

sher

ies

Ele

ctro

nic

– E

xcel

Nat

iona

lFi

sher

ies

Tech

nica

l Tea

m

Goo

dN

one

EA

Mid

land

sS

ever

n –

Sax

on's

Lode

SO

8633

3905

NA

Dai

ly m

eans

1975

–pre

sent

No

– sm

all g

aps

due

tobr

eakd

own

Unk

now

nFi

sher

ies

Ele

ctro

nic

– E

xcel

Nat

iona

lFi

sher

ies

Tech

nica

l Tea

m

Goo

dN

one

EA

Mid

land

sS

ever

n –

She

lton

(not

in u

se s

ince

1988

)

SJ4

8881

273

NA

Dai

ly m

eans

1975

–198

8N

o –

smal

l gap

sdu

e to

brea

kdow

n

Unk

now

nFi

sher

ies

Ele

ctro

nic

– E

xcel

Nat

iona

lFi

sher

ies

Tech

nica

l Tea

m

Goo

dN

one

EA

Mid

land

sS

ever

n –

Wel

shB

ridge

SJ4

8881

273

NA

Dai

ly m

eans

1989

–pre

sent

No

– sm

all g

aps

due

tobr

eakd

own

Unk

now

nFi

sher

ies

Ele

ctro

nic

– E

xcel

Nat

iona

lFi

sher

ies

Tech

nica

l Tea

m

Goo

dN

one

EC

N w

ebsi

teM

idla

nds

Bra

dgat

e B

rook

4522

00 3

099

NA

Wee

kly

1988

–200

3Ye

sYe

sM

onito

ring

Cen

tral O

racl

eda

taba

seC

EH

Lan

cast

er3

wee

ks£1

50 to

ext

ract

all

EC

N w

ebsi

teM

idla

nds

Lath

kill

4220

00 3

6470

0N

AW

eekl

y19

87–2

003

Yes

Yes

Mon

itorin

gC

entra

l Ora

cle

data

base

CE

H L

anca

ster

3 w

eeks

£150

to e

xtra

ctal

lLO

CA

RM

idla

nds

Coa

l Bro

ok –

Mar

ket D

rayt

on36

9300

334

100

NA

15 m

in15

/10/

2002

–08

/200

6Ye

sN

oLO

CA

RO

racl

e cs

vC

EH

Wal

lingf

ord

Goo

dN

o bu

t req

uire

spe

rmis

sion

LOC

AR

Mid

land

sTe

rn –

Ter

nhill

3628

00 3

3150

0N

A15

min

19/1

0/20

02–

08/2

006

Yes

No

LOC

AR

Ora

cle

csv

CE

H W

allin

gfor

dG

ood

No

but r

equi

res

perm

issi

onLO

CA

RM

idla

nds

Tern

– E

aton

on

Tern

3649

00 3

2320

0N

A15

min

09/1

0/20

02–

08/2

006

Yes

No

LOC

AR

Ora

cle

csv

CE

H W

allin

gfor

dG

ood

No

but r

equi

res

perm

issi

onLO

CA

RM

idla

nds

Tern

– N

orto

n-in

-H

ales

3707

00 3

3850

0N

A15

min

15/1

0/20

02–

08/2

006

Yes

No

LOC

AR

Ora

cle

csv

CE

H W

allin

gfor

dG

ood

No

but r

equi

res

perm

issi

onLO

CA

RM

idla

nds

Pot

ford

Bro

ok –

San

dyfo

rd B

ridge

3634

00 3

2220

0N

A15

min

16/1

0/20

02–

08/2

006

Yes

No

LOC

AR

Ora

cle

csv

CE

H W

allin

gfor

dG

ood

No

but r

equi

res

perm

issi

onLO

CA

RM

idla

nds

Bai

ley

Bro

ok –

Tern

hill

362

800

3315

00N

A15

min

19/1

0/20

02–

08/2

006

Yes

No

LOC

AR

Ora

cle

csv

CE

H W

allin

gfor

dG

ood

No

but r

equi

res

perm

issi

on

Mid

land

s La

ke

Dat

a so

urce

Reg

ion

Site

nam

eG

rid re

fSa

mpl

ing

dept

h(m

)Sa

mpl

ing

freq

uenc

yLe

ngth

of

reco

rdC

ontin

uous

reco

rd?

QA/

QC

Purp

ose

Stor

age

med

ium

Stor

age

loca

tion

Acce

ssib

ility

Cos

t

EA

Tw

erto

nM

idla

nds

78 s

ites

Incl

uded

Unk

now

nV

arie

s19

99–2

005

Var

ies

Yes

– M

IDA

SM

ultip

leE

lect

roni

c –

Ora

cle

dow

nloa

ded

to u

sas

Acc

ess

Twer

ton

Goo

dN

one

Scie

nce

Rep

ort C

limat

e ch

ange

impa

cts

and

wat

er te

mpe

ratu

re72N

orth

Eas

t Riv

er

Dat

a so

urce

Reg

ion

Site

nam

eG

rid re

fSa

mpl

ing

dept

h (m

)Sa

mpl

ing

freq

uenc

yLe

ngth

of r

ecor

dC

ontin

uous

reco

rd?

QA/

QC

Purp

ose

Stor

age

med

ium

Stor

age

loca

tion

Acce

ssib

ility

Cos

t

EA

Tw

erto

nN

orth

Eas

t36

52 s

ites

Incl

uded

NA

Var

ies

1965

–200

5V

arie

sYe

s –

MID

AS

Mul

tiple

Ele

ctro

nic

–O

racl

edo

wnl

oade

d to

us

as A

cces

s

Twer

ton

Goo

dN

one

EA

Nor

thum

bria

Nor

th E

ast

Riv

er T

yne

– U

gly

Dub

, Byw

ell,

Hay

don

Brid

ge

NA

NA

Dai

ly m

ean

1993

–pre

sent

Unk

now

nU

nkno

wn

Mon

itorin

gpd

fsE

A N

orth

umbr

iaG

ood

Non

e

EA

Nor

th E

ast

Riv

er T

ees

–Te

es B

arra

geN

Z 46

3190

NA

Hou

rly19

95–p

rese

ntS

ome

gaps

due

to lo

gger

failu

reN

oW

ater

tem

p/fis

hgr

owth

stu

dyE

xcel

Loca

l and

cen

tral

data

base

Rea

sona

ble

Non

e

EA

Nor

th E

ast

Riv

er T

ees

–Ya

rmN

Z 41

7132

NA

Hou

rly19

95–p

rese

ntS

ome

gaps

due

to lo

gger

failu

reN

oW

ater

tem

p/fis

hgr

owth

stu

dyE

xcel

Loca

l and

cen

tral

data

base

Rea

sona

ble

Non

e

EA

Nor

th E

ast

Riv

er T

ees

– Lo

wW

orsa

llN

Z 39

2103

NA

Hou

rly19

95–p

rese

ntS

ome

gaps

due

to lo

gger

failu

reN

oW

ater

tem

p/fis

hgr

owth

stu

dyE

xcel

Loca

l and

cen

tral

data

base

Rea

sona

ble

Non

e

EA

Nor

th E

ast

Riv

er T

ees

– Lo

wM

oor

NZ

3651

05N

AH

ourly

1995

–pre

sent

Som

e ga

ps d

ueto

logg

er fa

ilure

No

Wat

er te

mp/

fish

grow

th s

tudy

Exc

elLo

cal a

nd c

entra

lda

taba

seG

ood

Non

e

EA

Nor

th E

ast

Riv

er T

ees

–C

roft

NZ

2900

98N

AH

ourly

1995

–pre

sent

Som

e ga

ps d

ueto

logg

er fa

ilure

No

Wat

er te

mp/

fish

grow

th s

tudy

Exc

elLo

cal a

nd c

entra

lda

taba

seR

easo

nabl

eN

one

EA

Nor

th E

ast

Riv

er T

ees

–B

arna

rd C

astle

NZ

0451

67N

AH

ourly

1995

–pre

sent

Som

e ga

ps d

ueto

logg

er fa

ilure

No

Wat

er te

mp/

fish

grow

th s

tudy

Exc

elLo

cal a

nd c

entra

lda

taba

seG

ood

Non

e

EA

Nor

th E

ast

Riv

er T

ees

–M

iddl

eton

InTe

esda

le

NY

9482

51N

AH

ourly

1995

–pre

sent

Som

e ga

ps d

ueto

logg

er fa

ilure

No

Wat

er te

mp/

fish

grow

th s

tudy

Exc

elLo

cal a

nd c

entra

lda

taba

seG

ood

Non

e

EA

Nor

th E

ast

Riv

er H

umbe

r –C

orpo

ratio

n P

ier

TA 1

00 2

82N

A30

min

s19

/12/

1991

–pr

esen

t13

/09/

1994

–23

/07/

1995

and

17/8

/200

0–19

/9/2

000

Yes

Mon

itorin

gox

ygen

sag

Ele

ctro

nic

–W

ISK

IW

ISK

IG

ood

Non

e

EA

Nor

th E

ast

Riv

er O

use

–C

awoo

d B

ridge

SE

574

378

NA

30 m

ins

06/0

7/19

92–

pres

ent

15/1

2/19

94–

12/2

/199

5 an

d25

/10/

2001

–11

/01/

2002

Yes

Mon

itorin

gox

ygen

sag

Ele

ctro

nic

–W

ISK

IW

ISK

IG

ood

Non

e

EA

Nor

th E

ast

Riv

er H

umbe

r –B

lack

toft

Jetty

SE

843

242

NA

30 m

ins

10/0

9/19

91–

pres

ent

Ye

sM

onito

ring

oxyg

en s

agE

lect

roni

c –

WIS

KI

WIS

KI

Goo

dN

one

EA

Nor

th E

ast

Riv

er T

yne

–S

win

g B

ridge

NZ

2522

8 63

717

NA

30 m

ins

1995

–pre

sent

14/1

1/19

97–

18/5

/199

8 an

d2/

10/1

998–

1/4/

1999

Yes

Mon

itorin

gox

ygen

sag

Ele

ctro

nic

–W

ISK

IW

ISK

IG

ood

Non

e

EC

N w

ebsi

teN

orth

Eas

tC

oque

t42

36 6

050

NA

Wee

kly

1992

–200

5Ye

sYe

sM

onito

ring

Cen

tral O

racl

eda

taba

seC

EH

Lan

cast

er3

wee

ks£1

50 to

ext

ract

all

EC

N w

ebsi

teN

orth

Eas

tE

sk48

685

5081

6N

AW

eekl

y19

94–2

005

Yes

Yes

Mon

itorin

gC

entra

l Ora

cle

data

base

CE

H L

anca

ster

3 w

eeks

£150

to e

xtra

ctal

lE

CN

web

site

Nor

th E

ast

Trou

t Bec

k37

58 5

335

NA

Con

tinuo

usho

urly

1997

–200

4Ye

sYe

sM

onito

ring

Cen

tral O

racl

eda

taba

seC

EH

Lan

cast

er3

wee

ks£2

50 +

VA

T

CE

H (U

KE

DI)

Nor

th E

ast

Tees

3 si

tes

NA

Sam

plin

gfre

quen

cyun

know

n

1991

–199

8U

nkno

wn

Unk

now

nE

ffect

of b

arra

geon

coa

rse

fish

Exc

elH

ard

disk

CE

HD

orse

tR

aw d

ata

not

acce

ssib

leU

nkno

wn

CE

H L

and

Oce

anIn

tera

ctio

n S

tudy

(LO

IS)

Nor

th E

ast

Hun

dred

s of

site

s, H

umbe

rB

asin

NA

NA

15 m

in to

mon

thly

1980

s on

war

dsN

o –

rand

omin

terv

als

QC

'dLO

ISC

entra

l Ora

cle

data

base

CE

H W

allin

gfor

dV

isit

requ

ired

Pos

sibl

e ch

arge

for s

taff

time

Nor

th E

ast L

ake

Dat

a so

urce

Reg

ion

Site

nam

eG

rid re

fSa

mpl

ing

dept

h(m

)Sa

mpl

ing

freq

uenc

yLe

ngth

of

reco

rdC

ontin

uous

reco

rd?

QA/

QC

Purp

ose

Stor

age

med

ium

Stor

age

loca

tion

Acce

ssib

ility

Cos

t

EA

Tw

erto

nN

orth

Eas

t33

site

sIn

clud

edU

nkno

wn

Var

ies

1979

–200

5V

arie

sYe

s –

MID

AS

Mul

tiple

Ele

ctro

nic

–O

racl

edo

wnl

oade

d to

us

as A

cces

s

Twer

ton

Goo

dN

one

Scie

nce

Rep

ort C

limat

e ch

ange

impa

cts

and

wat

er te

mpe

ratu

re73

Nor

th W

est R

iver

Dat

a so

urce

Reg

ion

Site

nam

eG

rid re

fSa

mpl

ing

dept

h (m

)Sa

mpl

ing

freq

uenc

yLe

ngth

of r

ecor

dC

ontin

uous

reco

rd?

QA/

QC

Purp

ose

Stor

age

med

ium

Stor

age

loca

tion

Acce

ssib

ility

Cos

t

EA

Tw

erto

nN

orth

Wes

t30

73 s

ites

Incl

uded

NA

Var

ies

1960

–200

5V

arie

sYe

s –

MID

AS

Mul

tiple

Ele

ctro

nic

–O

racl

edo

wnl

oade

d to

us

as A

cces

s

Twer

ton

Goo

dN

one

EA

Nor

th W

est

Riv

er L

une

–Ly

on B

ridge

SD

581

5 69

71N

AV

aria

ble

Feb

80–D

ec 9

9(m

ay b

e av

aila

ble

afte

r thi

s da

te)

No

Not

kno

wn

Not

kno

wn

Exc

elLo

cal h

ard

driv

eG

ood

Non

e

EA

Nor

th W

est

Riv

er L

une

–Fo

rge

Wei

rS

D 5

1342

647

16N

AH

ourly

1999

–pre

sent

Som

e ga

ps >

1m

onth

(200

0 an

d20

04)

Pro

be c

alib

rate

dev

ery

3–6

mon

ths

Fish

mov

emen

tM

ostly

ele

ctro

nic

exce

lLo

cal e

xter

nal

driv

eYe

sN

one

EA

Nor

th W

est

Riv

er E

sk –

Cro

pple

How

SD

131

00 9

7770

NA

15-m

inut

e15

/11/

1989

–26

/11/

2004

Som

e ga

psN

ot fo

r tem

p. –

poor

con

ditio

nW

ater

qua

lity

Ele

ctro

nic

–W

ISK

IW

ISK

IG

ood

Non

e

EA

Nor

th W

est

Riv

er D

uddo

n –

Dud

don

Hal

lS

D 1

9560

895

70N

A15

-min

ute

20/1

1/19

94–

09/1

1/20

04S

ome

gaps

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EC

N w

ebsi

teS

outh

Wes

tFr

ome

3891

867

0N

AW

eekl

y19

94–2

005

Yes

Yes

Mon

itorin

gC

entra

l Ora

cle

data

base

CE

H L

anca

ster

3 w

eeks

£150

to e

xtra

ctal

lLO

CA

RS

outh

Wes

tB

ere

Stre

am –

Sna

tford

Brid

ge38

5575

, 092

975

NA

15 m

inut

es13

/11/

2002

–09

/200

6Ye

sN

oLO

CA

RO

racl

e cs

vC

EH

Wal

lingf

ord

Goo

dN

o bu

t req

uire

spe

rmis

sion

LOC

AR

Sou

th W

est

Bov

ingt

on S

tream

– B

lindm

ans

Woo

d

3841

75, 0

8780

0N

A15

min

utes

01/1

0/20

02–

09/2

006

Yes

No

LOC

AR

Ora

cle

csv

CE

H W

allin

gfor

dG

ood

No

but r

equi

res

perm

issi

on

LOC

AR

Sou

th W

est

Dev

ils B

rook

–D

ewlis

h vi

llage

3778

00, 0

9850

0N

A15

min

utes

23/1

1/20

02–

09/2

006

Yes

No

LOC

AR

Ora

cle

csv

CE

H W

allin

gfor

dG

ood

No

but r

equi

res

perm

issi

onLO

CA

RS

outh

Wes

tFr

ome

– E

ast

Sto

ke38

6725

, 086

850

NA

15 m

inut

es30

/08/

2002

–09

/200

6Ye

sN

oLO

CA

RO

racl

e cs

vC

EH

Wal

lingf

ord

Goo

dN

o bu

t req

uire

spe

rmis

sion

LOC

AR

Sou

th W

est

From

e –

Loud

smill

3708

50, 0

9047

5N

A15

min

utes

02/1

0/20

02–

09/2

006

Yes

No

LOC

AR

Ora

cle

csv

CE

H W

allin

gfor

dG

ood

No

but r

equi

res

perm

issi

onLO

CA

RS

outh

Wes

tFr

ome

–C

hilfr

ome

3590

50, 0

9912

5N

A15

min

utes

03/0

2/20

03–

09/2

006

Yes

No

LOC

AR

Ora

cle

csv

CE

H W

allin

gfor

dG

ood

No

but r

equi

res

perm

issi

onLO

CA

RS

outh

Wes

tP

iddl

e –

Bag

gsM

ill39

1325

, 087

600

NA

15 m

inut

es30

/10/

2003

–09

/200

6Ye

sN

oLO

CA

RO

racl

e cs

vC

EH

Wal

lingf

ord

Goo

dN

o bu

t req

uire

spe

rmis

sion

LOC

AR

Sou

th W

est

Pid

dle

–B

riant

spud

dle

3821

25, 0

9345

0N

A15

min

utes

23/1

1/20

02–

09/2

006

Yes

No

LOC

AR

Ora

cle

csv

CE

H W

allin

gfor

dG

ood

No

but r

equi

res

perm

issi

onLO

CA

RS

outh

Wes

tP

iddl

e –

Littl

eP

uddl

e37

1850

, 096

450

NA

15 m

inut

es31

/10/

2002

–09

/200

6Ye

sN

oLO

CA

RO

racl

e cs

vC

EH

Wal

lingf

ord

Goo

dN

o bu

t req

uire

spe

rmis

sion

LOC

AR

Sou

th W

est

Syd

ling

Wat

er –

Syd

ling

St.

Nic

hola

s

3632

25, 0

9990

0N

A15

min

utes

23/1

2/20

02–

09/2

006

Yes

No

LOC

AR

Ora

cle

csv

CE

H W

allin

gfor

dG

ood

No

but r

equi

res

perm

issi

on

LOC

AR

Sou

th W

est

Hoo

ke –

Mai

den

New

ton

3594

75, 0

9760

0N

A15

min

utes

05/0

3/20

03–

09/2

006

Yes

No

LOC

AR

Ora

cle

csv

CE

H W

allin

gfor

dG

ood

No

but r

equi

res

perm

issi

onC

EH

(UK

ED

I)S

outh

Wes

tR

iver

Wyl

yeU

nkno

wn

NA

Ann

ually

10/1

996

onw

ards

Unk

now

nU

nkno

wn

Gra

ylin

gpo

pula

tion

stud

yA

cces

s/E

xcel

Har

d di

sk C

EH

Dor

set

Raw

dat

a no

tac

cess

ible

Unk

now

n

CE

H (U

KE

DI)

Sou

th W

est

Mill

Stre

amU

nkno

wn

NA

Wee

kly

1991

–199

7U

nkno

wn

Unk

now

nC

hem

ical

sam

plin

gE

xcel

Net

wor

k D

rive

CE

H D

orse

tR

aw d

ata

acce

ssib

leU

nkno

wn

CE

H (U

KE

DI)

Sou

th W

est

Eas

t Sto

keFl

ume,

Riv

erFr

ome

Unk

now

nN

AD

aily

max

and

min

1973

–198

9U

nkno

wn

Unk

now

nR

iver

Fro

me

envi

ronm

enta

lda

ta

Unk

now

nU

nkno

wn

Raw

dat

a no

tac

cess

ible

Unk

now

n

CE

H (U

KE

DI)

Sou

th W

est

Riv

er F

rom

e, E

ast

Sto

keU

nkno

wn

NA

15 m

inut

es19

95–p

rese

ntU

nkno

wn

Unk

now

nR

iver

Fro

me

salm

on c

ount

erE

xcel

Har

d di

sk C

EH

Dor

set

Raw

dat

aac

cess

ible

Unk

now

n

CE

H (U

KE

DI)

Sou

th W

est

Gus

sage

Stre

amU

nkno

wn

NA

Var

iabl

e, n

otfre

quen

t19

73–1

976

Unk

now

nU

nkno

wn

Eco

logi

cal

reco

very

of

Gus

sage

Stre

am

Unk

now

nU

nkno

wn

Raw

dat

a no

tac

cess

ible

Unk

now

n

Uni

vers

ity o

fE

xete

rS

outh

Wes

t17

trib

utar

ies

NA

NA

15 m

inut

es to

hour

ly19

76/1

977

onw

ards

No

Not

all

Res

earc

hE

lect

roni

cE

xete

rW

ill n

ot p

ass

onto

third

par

ties

N/A

Bou

rnem

outh

and

Wes

t Han

tsW

ater

Sou

th W

est

Kna

pp M

illU

nkno

wn

NA

15 m

inut

es20

04–p

rese

nt U

nkno

wn

Che

cked

by

Env

ironm

ent

Age

ncy

Wat

er c

ompa

nym

onito

ring

Unk

now

nU

nkno

wn

Unk

now

nU

nkno

wn

EA

Sou

th W

est

Ham

pshi

re A

von

– A

mes

bury

SU

151

413

NA

15 m

inut

es13

/02/

2004

–pr

esen

t U

nkno

wn

No

Unk

now

nE

lect

roni

cW

ISK

IG

ood

Non

e

EA

Sou

th W

est

Ham

pshi

re A

von

– E

ast M

ills

SU

158

144

NA

15 m

inut

es18

/05/

2004

–pr

esen

t U

nkno

wn

No

Unk

now

nE

lect

roni

cW

ISK

IG

ood

Non

e

EA

Sou

th W

est

Riv

er S

tour

–H

amm

oon

Unk

now

nN

A15

min

utes

24/0

3/20

04–

pres

ent

Unk

now

nN

oU

nkno

wn

Ele

ctro

nic

WIS

KI

Goo

dN

one

EA

Sou

th W

est

Riv

er S

tour

–Th

roop

Unk

now

nN

A15

min

utes

24/0

5/20

00–

pres

ent

Unk

now

nN

oU

nkno

wn

Ele

ctro

nic

WIS

KI

Goo

dN

one

EA

Sou

th W

est

Riv

er T

amar

shel

lfish

SX

4380

0610

00N

AA

ppro

x m

onth

ly20

/04/

1999

–pr

esen

tS

ome

gaps

(mis

sing

mon

ths)

Unk

now

nU

nkno

wn

Ele

ctro

nic

WIS

KI

Goo

dN

one

EA

Sou

th W

est

RIv

er T

amar

–G

unni

slak

eB

ridge

SX

4349

3724

36N

AV

aria

ble

(eve

ry 3

days

to m

onth

ly)

08/0

1/19

86–

pres

ent

Occ

asio

nal

mis

sing

mon

ths

Unk

now

nU

nkno

wn

Ele

ctro

nic

WIS

KI

Goo

dN

one

EA

Sou

th W

est

Riv

er T

avy–

Lopw

ell D

amS

X47

5006

5038

NA

Var

iabl

e (w

eekl

yto

mon

thly

)09

/01/

1986

–pr

esen

tO

ccas

iona

lm

issi

ng m

onth

sU

nkno

wn

Unk

now

nE

lect

roni

cW

ISK

IG

ood

Non

e

Scie

nce

Rep

ort C

limat

e ch

ange

impa

cts

and

wat

er te

mpe

ratu

re77

Dat

a so

urce

Reg

ion

Site

nam

eG

rid re

fSa

mpl

ing

dept

h (m

)Sa

mpl

ing

freq

uenc

yLe

ngth

of

reco

rdC

ontin

uous

reco

rd?

QA/

QC

Purp

ose

Stor

age

med

ium

Stor

age

loca

tion

Acce

ssib

ility

Cos

t

EA

Sou

th W

est

Ham

pshi

re A

von

– E

ast M

ills

SU

1587

1430

NA

15 m

inut

es18

/05/

04–

pres

ent

Gap

sYe

sFi

sher

ies

Ele

ctro

nic

WIS

KI

Goo

dN

one

EA

Sou

th W

est

Riv

er S

tour

–Th

roop

SZ1

1309

580

NA

15 m

inut

es24

/05/

00–

pres

ent

Gap

sYe

sFi

sher

ies

Ele

ctro

nic

WIS

KI

Goo

dN

one

Sout

h W

est L

ake

Dat

a so

urce

Reg

ion

Site

nam

eG

rid re

fSa

mpl

ing

dept

h(m

)Sa

mpl

ing

freq

uenc

yLe

ngth

of

reco

rdC

ontin

uous

reco

rd?

QA/

QC

Purp

ose

Stor

age

med

ium

Stor

age

loca

tion

Acce

ssib

ility

Cos

t

EA

Tw

erto

nS

outh

Wes

t22

2 si

tes

Incl

uded

Unk

now

nV

arie

s19

81–2

005

Var

ies

Yes

– M

IDA

SM

ultip

leE

lect

roni

c –

Ora

cle

dow

nloa

ded

to u

sas

Acc

ess

Twer

ton

Goo

dN

one

Scie

nce

Rep

ort C

limat

e ch

ange

impa

cts

and

wat

er te

mpe

ratu

re78Th

ames

Riv

er

Dat

a so

urce

Reg

ion

Site

nam

eG

rid re

fSa

mpl

ing

dept

h (m

)Sa

mpl

ing

freq

uenc

yLe

ngth

of r

ecor

dC

ontin

uous

reco

rd?

QA/

QC

Purp

ose

Stor

age

med

ium

Stor

age

loca

tion

Acce

ssib

ility

Cos

t

EA

Tw

erto

nTh

ames

2086

site

sIn

clud

edN

AV

arie

s19

72–2

005

Var

ies

Yes

– M

IDA

SM

ultip

leE

lect

roni

c –

Ora

cle

Twer

ton

Goo

dN

one

EA

Tha

mes

Tham

es70

site

s, T

ham

esan

d tri

bs (T

idew

ayIn

form

atio

nM

anag

emen

tS

yste

m)

NA

NA

15 m

ins–

1 ho

ur10

+ y

ears

bac

kS

ome

dow

ntim

esN

o –

raw

dat

a,he

alth

war

ning

!M

onito

ring

Exc

elR

eadi

ngG

ood

Non

e

EA

Tham

esR

iver

Tha

mes

–Te

ddin

gton

TQ 1

670

7150

NA

Up

to 2

4 ho

urly

read

ings

per

day

(aut

omat

ic)

June

86–

Dec

2000

(may

be

avai

labl

e af

ter

this

dat

e)

Oct

–-D

ec 1

986;

Apr

–-M

ay 1

988;

Jan–

Dec

199

1;A

pr 1

992;

Feb

–M

ay 1

995;

Aug

–D

ec 2

000

Not

kno

wn

Not

kno

wn

Exc

elLo

cal h

ard

driv

eG

ood

Non

e

EC

N w

ebsi

teTh

ames

Col

n42

04 1

988

NA

Wee

kly

1998

–200

5N

o –

2001

mis

sing

Yes

Mon

itorin

gC

entra

l Ora

cle

data

base

CE

H L

anca

ster

3 w

eeks

£150

to e

xtra

ct a

ll

EC

N w

ebsi

teTh

ames

Lam

bour

n44

53 1

691

NA

Wee

kly

1998

–200

5Ye

sYe

sM

onito

ring

Cen

tral O

racl

eda

taba

seC

EH

Lan

cast

er3

wee

ks£1

50 to

ext

ract

all

LOC

AR

Tham

esLa

mbo

urn

– E

ast

She

fford

4389

50, 1

7455

0N

A15

min

03/0

8/20

03Ye

sN

oLO

CA

RO

racl

e cs

vC

EH

Wal

lingf

ord

Goo

dN

o bu

t req

uire

spe

rmis

sion

LOC

AR

Tham

esLa

mbo

urn

– S

haw

4470

00, 1

6820

0N

A15

min

04/1

1/20

03Ye

sN

oLO

CA

RO

racl

e cs

vC

EH

Wal

lingf

ord

Goo

dN

o bu

t req

uire

spe

rmis

sion

LOC

AR

Tham

esP

ang

– B

uckl

ebur

y45

5300

, 171

000

NA

15 m

in30

/10/

2002

–31

/08/

2006

Yes

No

LOC

AR

Ora

cle

csv

CE

H W

allin

gfor

dG

ood

No

but r

equi

res

perm

issi

onLO

CA

RTh

ames

Pan

g –

Frils

ham

(Par

sona

ge)

4537

50, 1

7300

0N

A15

min

14/1

0/20

02Ye

sN

oLO

CA

RO

racl

e cs

vC

EH

Wal

lingf

ord

Goo

dN

o bu

t req

uire

spe

rmis

sion

LOC

AR

Tham

esP

ang

– Ti

dmar

shM

ill46

3600

, 174

775

NA

15 m

in30

/10/

2002

Yes

No

LOC

AR

Ora

cle

csv

CE

H W

allin

gfor

dG

ood

No

but r

equi

res

perm

issi

onLO

CA

RTh

ames

Pan

g –

belo

w B

lue

Poo

l45

8675

, 171

850

NA

15 m

in03

/08/

2003

–29

/08/

2006

Yes

No

LOC

AR

Ora

cle

csv

CE

H W

allin

gfor

dG

ood

No

but r

equi

res

perm

issi

onC

EH

(UK

ED

I)Th

ames

Lam

bour

nU

nkno

wn

NA

Mon

thly

03/1

994–

03/1

997

Unk

now

nU

nkno

wn

Eco

logi

cal s

tudy

of c

halk

stre

ams

Unk

now

nU

nkno

wn

Raw

dat

a no

tac

cess

ible

Unk

now

n

CE

H (U

KE

DI)

Tham

esC

oln

Unk

now

nN

AM

onth

ly03

/197

8–03

/197

9U

nkno

wn

Unk

now

nE

colo

gica

l stu

dyof

cha

lk s

tream

sU

nkno

wn

Unk

now

nR

aw d

ata

not

acce

ssib

leU

nkno

wn

Tham

es L

ake

Dat

a so

urce

Reg

ion

Site

nam

eG

rid re

fSa

mpl

ing

dept

h(m

)Sa

mpl

ing

freq

uenc

yLe

ngth

of

reco

rdC

ontin

uous

reco

rd?

QA/

QC

Purp

ose

Stor

age

med

ium

Stor

age

loca

tion

Acce

ssib

ility

Cos

t

EA

Tw

erto

nTh

ames

106

site

sIn

clud

edU

nkno

wn

Var

ies

1979

–200

5V

arie

sYe

s –

MID

AS

Mul

tiple

Ele

ctro

nic

–O

racl

edo

wnl

oade

d to

us

as A

cces

s

Twer

ton

Goo

dN

one

Scie

nce

Rep

ort C

limat

e ch

ange

impa

cts

and

wat

er te

mpe

ratu

re79

Wal

es R

iver

Dat

a so

urce

Reg

ion

Site

nam

eG

rid re

fSa

mpl

ing

dept

h (m

)Sa

mpl

ing

freq

uenc

yLe

ngth

of r

ecor

dC

ontin

uous

reco

rd?

QA/

QC

Purp

ose

Stor

age

med

ium

Stor

age

loca

tion

Acce

ssib

ility

Cos

t

EA

Tw

erto

nW

ales

1436

site

sIn

clud

edN

AV

arie

s19

62–2

005

Var

ies

Yes

– M

IDA

SM

ultip

leE

lect

roni

c –

Ora

cle

dow

nloa

ded

to u

sas

Acc

ess

Twer

ton

Goo

dN

one

EC

N w

ebsi

teW

ales

Wye

3536

209

9N

AW

eekl

y19

94–2

005

Yes

Yes

Mon

itorin

gC

entra

l Ora

cle

data

base

CE

H L

anca

ster

3 w

eeks

£150

to e

xtra

ct a

ll

CE

H (U

KE

DI)

Wal

esA

fon

Hor

e, A

fon

Haf

fren,

Afo

nC

wm

Unk

now

nN

AS

ampl

ing

frequ

ency

unkn

own

Dat

es u

nkno

wn

Unk

now

nU

nkno

wn

Afo

n C

wm

fish

coun

ter

Exc

elH

ard

disk

CE

HD

orse

tR

aw d

ata

not

acce

ssib

leU

nkno

wn

CH

AS

MW

ales

Sev

ern

– D

ulas

at

Cen

arth

Mill

2975

5 27

767

NA

15 m

in14

/03/

2003

–pr

esen

tYe

s ap

art f

rom

equi

pmen

t fai

lure

No

CH

AS

ME

lect

roni

c cs

vD

atab

ase

Goo

dP

erm

issi

onre

quire

d, p

ossi

ble

char

geC

HA

SM

Wal

esS

ever

n –

Dul

as –

Nan

t Wau

n-fa

ch29

660

2779

0N

A15

min

14/0

3/20

03–

pres

ent

Yes

apar

t fro

meq

uipm

ent f

ailu

reN

oC

HA

SM

Ele

ctro

nic

csv

Dat

abas

eG

ood

Per

mis

sion

requ

ired,

pos

sibl

ech

arge

CH

AS

MW

ales

Sev

ern

– D

ulas

–N

ant y

Sae

son

2949

0 27

685

NA

15 m

in14

/03/

2005

–pr

esen

tYe

s ap

art f

rom

equi

pmen

t fai

lure

No

CH

AS

ME

lect

roni

c cs

vD

atab

ase

Goo

dP

erm

issi

onre

quire

d, p

ossi

ble

char

geC

HA

SM

Wal

esS

ever

n –

Low

erH

afre

n28

430

2878

0N

A15

min

8/3/

05–2

8/9/

05Ye

s ap

art f

rom

equi

pmen

t fai

lure

No

CH

AS

ME

lect

roni

c cs

vD

atab

ase

Goo

dP

erm

issi

onre

quire

d, p

ossi

ble

char

geC

HA

SM

Wal

esS

ever

n –

Tanl

lwyt

h28

400

2877

0N

A15

min

8/3/

05–2

8/9/

05Ye

s ap

art f

rom

equi

pmen

t fai

lure

No

CH

AS

ME

lect

roni

c cs

vD

atab

ase

Goo

dP

erm

issi

onre

quire

d, p

ossi

ble

char

geC

HA

SM

Wal

esS

ever

n –

Upp

erH

afre

n28

280

2893

0N

A15

min

8/3/

05–1

0/8/

05Ye

s ap

art f

rom

equi

pmen

t fai

lure

No

CH

AS

ME

lect

roni

c cs

vD

atab

ase

Goo

dP

erm

issi

onre

quire

d, p

ossi

ble

char

geE

AW

ales

Riv

er T

ryw

eryn

dow

nstre

am L

lyn

Cel

yn (D

ee)

SH

880

399

NA

Dai

ly m

ax/m

in(c

ontin

uous

char

t) 19

79–2

000

Jul 1

979–

Jan

2000

Apr

199

0–Ju

ne19

95 –

gap

s >

1m

onth

Che

cked

200

3on

war

dsP

ost-r

egul

atio

nm

onito

ring

prog

ram

me

Exc

elLo

cal h

ard

driv

eG

ood

Non

e

EA

Wal

esR

iver

Try

wer

yndo

wns

tream

Lly

nC

elyn

(Dee

)

SH

880

399

NA

15-m

in re

adin

gs(a

utom

atic

)20

03–p

rese

nt

Oct

200

3–pr

esen

tA

pr 1

990–

June

1995

– g

aps

> 1

mon

th

Che

cked

200

3on

war

dsP

ost-r

egul

atio

nm

onito

ring

prog

ram

me

Exc

elLo

cal h

ard

driv

eG

ood

Non

e

EA

Wal

esR

iver

Dee

– B

ala

slui

ces

SH

936

356

NA

Dai

ly m

ax/m

in(c

ontin

uous

char

t)

1990

–200

019

90–2

000

Che

cked

200

3on

war

dsP

ost-r

egul

atio

nm

onito

ring

prog

ram

me

Exc

elLo

cal h

ard

driv

eG

ood

Non

e

EA

Wal

esR

iver

Dee

– B

ala

slui

ces

SH

936

356

NA

15-m

in re

adin

gs(a

utom

atic

)

2003

–pre

sent

Che

cked

200

3on

war

dsP

ost-r

egul

atio

nm

onito

ring

prog

ram

me

Exc

elLo

cal h

ard

driv

eG

ood

Non

e

EA

Wal

esR

iver

Dee

–M

anle

y H

all

SJ

3481

414

6N

AD

aily

max

/min

(con

tinuo

usch

art)

1965

–199

9

2003

–pre

sent

Feb–

May

200

5 –

gaps

> 1

mon

thC

heck

ed 2

002

onw

ards

Pos

t-reg

ulat

ion

mon

itorin

gpr

ogra

mm

e

Exc

elLo

cal h

ard

driv

eG

ood

Non

e

EA

Wal

esR

iver

Dee

–M

anle

y H

all

SJ

3481

414

6N

A15

-min

read

ings

(aut

omat

ic)

2002

–pre

sent

June

200

2–pr

esen

tFe

b–M

ay 2

005

–ga

ps >

1 m

onth

Che

cked

200

2on

war

dsP

ost-r

egul

atio

nm

onito

ring

prog

ram

me

Exc

elLo

cal h

ard

driv

eG

ood

Non

e

EA

Wal

esR

iver

Wye

–R

edbr

ook

SO

528

6 11

08N

AD

aily

9am

Jan

96–D

ec 2

000

(may

be

data

avai

labl

e af

ter

this

dat

e)

Oct

–Nov

200

0 –

gaps

> 1

mon

thS

ome

chec

king

for s

purio

usre

adin

gs

Not

kno

wn

Exc

elLo

cal h

ard

driv

eG

ood

Non

e

EA

Wal

esR

iver

Taf

f –B

lack

wei

rS

T170

60 7

8053

NA

30 m

in –

hou

rly19

93–p

rese

nt19

96 m

onth

lym

eans

onl

y, 1

997

mis

sing

Aug

–Dec

Som

e cr

oss

chec

king

Car

diff

Bay

fishe

ries

mon

itorin

gpr

ojec

t

Ele

ctro

nic

– E

xcel

Loca

l G d

rive

Goo

dN

one

EA

Wal

esW

ye –

Bel

mon

tS

O 4

8500

387

99N

A15

-min

ute

14/0

1/19

97–

pres

ent

Oct

-Dec

199

7U

p to

200

0U

nkno

wn

Ele

ctro

nic

WIS

KI

Goo

dN

one

EA

Wal

esU

sk –

Tra

llong

SN

947

26 2

9547

NA

15-m

inut

eJu

ne 2

004–

pres

ent

Yes

No

Unk

now

nE

lect

roni

cW

ISK

IG

ood

but n

ot in

publ

ic d

omai

nN

one

EA

Wal

esW

ye –

Lla

ndew

iS

O 1

0458

682

84N

A15

-min

ute

Nov

200

1–da

teJa

n–M

ay 2

004

No

Unk

now

nE

lect

roni

cW

ISK

IG

ood

but n

ot in

publ

ic d

omai

nN

one

EA

Wal

esW

ye –

Red

broo

kS

O 5

2769

110

77N

A15

-min

ute

Jan

1993

–pr

esen

tJu

ne–O

ctob

er19

93, M

ay–

Sep

tem

ber 1

995

Up

to 2

001

Unk

now

nE

lect

roni

cW

ISK

IG

ood

Non

e

EA

Wal

esW

ye –

Erw

ood

SO

075

80 4

4490

NA

15-m

inut

eJu

ne 1

993–

Sep

t19

95O

ctob

er 2

000–

July

200

1U

p to

200

1U

nkno

wn

Ele

ctro

nic

WIS

KI

Goo

d bu

t not

inpu

blic

dom

ain

Non

e

EA

Wal

esTy

wi –

Cap

elD

ewi,

Felin

Myn

achd

y,M

anor

avon

,D

olau

hirio

n,Ys

tradf

fin

Var

ious

NA

15-m

inut

e01

/06/

1997

–pr

esen

tYe

sN

oU

nkno

wn

Ele

ctro

nic

WIS

KI

Goo

dN

one

EA

Wal

esD

eeS

H 8

8077

399

39N

A15

-min

ute

11/0

3–da

teU

nkno

wn

Som

eU

nkno

wn

Ele

ctro

nic

Unk

now

nG

ood

Non

e

Scie

nce

Rep

ort C

limat

e ch

ange

impa

cts

and

wat

er te

mpe

ratu

re80D

ata

sour

ceR

egio

nSi

te n

ame

Grid

ref

Sam

plin

gde

pth

(m)

Sam

plin

gfr

eque

ncy

Leng

th o

f rec

ord

Con

tinuo

usre

cord

?Q

A/Q

CPu

rpos

eSt

orag

e m

ediu

mSt

orag

elo

catio

nAc

cess

ibili

tyC

ost

EA

Wal

esD

eeS

H 7

4087

357

21N

A15

-min

ute

11/0

3–da

teU

nkno

wn

Som

eU

nkno

wn

Ele

ctro

nic

Unk

now

nG

ood

Non

eE

AW

ales

Dee

SJ

3482

2 41

459

NA

15-m

inut

e06

/02–

date

Unk

now

nS

ome

Unk

now

nE

lect

roni

c U

nkno

wn

Goo

dN

one

EA

Wal

esD

eeS

J 41

764

6002

3N

A15

-min

ute

11/0

3–da

teU

nkno

wn

Som

eU

nkno

wn

Ele

ctro

nic

Unk

now

nG

ood

Non

eE

AW

ales

Dee

SJ

2904

6 70

696

NA

15-m

inut

e12

/95–

date

Unk

now

nS

ome

Unk

now

nE

lect

roni

c U

nkno

wn

Goo

dN

one

Wal

es L

ake

Dat

a so

urce

Reg

ion

Site

nam

eG

rid re

fSa

mpl

ing

dept

h(m

)Sa

mpl

ing

freq

uenc

yLe

ngth

of

reco

rdC

ontin

uous

reco

rd?

QA/

QC

Purp

ose

Stor

age

med

ium

Stor

age

loca

tion

Acce

ssib

ility

Cos

t

EA

Tw

erto

nW

ales

60 s

ites

Incl

uded

Unk

now

nV

arie

s19

78–2

005

Var

ies

Yes

– M

IDA

SM

ultip

leE

lect

roni

c –

Ora

cle

dow

nloa

ded

to u

sas

Acc

ess

Twer

ton

Goo

dN

one

EC

N w

ebsi

teW

ales

Llyn

Lla

gi26

48 3

484

Unk

now

nFo

rtnig

htly

1990

–200

5N

o –

1991

–199

4an

d 19

96–1

999

mis

sing

Yes

Mon

itorin

gC

entra

l Ora

cle

data

base

CE

H L

anca

ster

3 w

eeks

£150

to e

xtra

ctal

l


Appendix CList of river sites analysed

Anglian Region

Site NGR Typology

Start date End date Missing datapoints

Monthly dataR.StourGt.Bradley HallBridge

TL6755052328

2 15/03/1983

05/12/2005

94

R.StourGt.WrattingFord

TL6912548424

2 15/04/1981

05/12/2005

29

R.StourKedington GS

TL7092145234

2 15/04/1981

05/12/2005

24

R.Stour AshenRoad BridgeClare

TL7680044899

5 22/07/1981

07/12/2005

82

R.StourBallingdon Br.

TL8671740988

5 30/03/1981

02/12/2005

18

R.StourBrundon Mill

TL8652442275

5 22/04/1981

02/12/2005

91

R.Stour BuresBr.

TL9061434062

5 15/04/1981

02/12/2005

24

R.Stour FlatfordMill Footbridge

TM0754333348

5 02/09/1981

14/12/2005

83

R.StourLangham Intake

TM0260834523

5 30/03/1981

30/11/2005

5

R.Stour ListonWeir

TL8566044992

5 15/04/1981

02/12/2005

30

R.Stour PentlowBr.

TL8109546410

5 15/04/1981

07/12/2005

24

R.Stour PitmereRailway Bridge

TL8907136915

5 21/07/1981

02/12/2005

78

R.StourStratford StMary Intake

TM0422534270

5 30/03/1981

15/12/2005

14

R.Stour WixoeWqms IntakePier

TL7083643102

5 30/03/1981

15/12/2005

7

R.StourCattawadeIntake

TM1003033044

0 30/03/1981

14/12/2005

19

R.Ouse A422Rd.Br.Brackley

SP5942736819

2 23/04/1981

14/11/2005

30

R.Ouse A5Rd.Br.OldStratford

SP7813040962

5 21/05/1981

29/11/2005

39

R.Ouse B526 SP877874420 5 14/04/198 29/11/200 45


Site NGR Typology


Rd.Br.NewportPagnell

9 1 5

R.Ouse WaterStratford Rd.Br.

SP6520534067

5 29/11/1994

14/11/2005

8

R.Ouse WqmsFoxcote Intake

SP7275534636

5 03/01/1986

14/11/2005

32

R.OuseClapham Intake

TL0360051600

8 30/11/1988

14/12/2005

34

R.OuseKempston Mill

TL0240047700

8 07/05/1981

13/12/2005

31

R.OuseNewnhamFt.Fb.

TL0637249294

8 12/05/1981

13/12/2005

38

R.Ouse OffordIntake

TL2140066200

8 14/04/1981

17/11/2005

20

R.OuseRavenstone Mill

SP8540048600

8 07/05/1981

01/12/2005

88

R.Ouse RoxtonLock

TL1600053500

8 14/04/1981

13/12/2005

23

R.OuseSharnbrook Mill

TL0110059000

8 14/04/1981

01/12/2005

30

R.Ouse St IvesRd.Br.

TL3130071200

8 21/04/1981

12/12/2005

58

R.OuseTyringhamBridge

SP8580046500

8 19/07/1984

05/12/2005

68

R.Ouse EatonSocon Mill

TL1750058500

0 12/05/1981

06/12/2005

83

Running WatersRuxox Bridge

TL0440036400

1 23/06/1981

08/12/2005

80

Running WatersA5120Rd.Br.Flitwick

TL0290036400

1 23/06/1981

08/12/2005

133

Hundred FootRiver EarithRd.Br.

TL3940074700

2 21/04/1981

28/11/2005

27

R.ThurneMartham Ferry

TG4450019500

2 20/01/1983

12/12/2005

10

Whittlesey DykeTurning TreeBridge

TL2820095600

3 17/11/1981

30/11/2005

80

Bevills LeamChapel Bridge

TL2890094100

3 25/06/1981

30/11/2005

90

R.BlackwaterLangford Intake

TL8364509179

5 30/03/1981

01/12/2005

10

R.ChelmerLangford Intake

TL8341108624

5 30/03/1981

01/12/2005

12

Middle LevelMDMullicourtPriory Sluice

TF5310002900

6 21/04/1981

17/11/2005

23


Site NGR Typology


Forty Foot R.Forty FootBr.Ramsey

TL3080088100

6 14/05/1981

14/12/2005

47

R.NeneWansford OldRd.Br.

TL0750099100

8 07/04/1981

24/11/2005

17

R.Nene Dog ina Doublet Sluice

TL2699999257

8 14/04/1981

24/11/2005

32

Ramsey RiverParkestonRd.Br.

TM2382131610

40 02/04/1981

22/11/2005

26

Spickets Bk.inletto the Mere

TL8680608571

40 04/04/1984

06/12/2005

17

Daily dataNB: Daily data reportedly do exist for Anglian but were not made available to Entec forthis report

Midlands Region

Site NGR Typology Start date End date GapsMonthly dataR.Severn atAtcham

SJ5400009300

7 08/02/1988 08/12/2005 12

R.Severn atBewdley

SO7875075450

7 04/01/1988 12/12/2005 9

R.Severn atBuildwas

SJ6450004400

7 16/02/1988 08/12/2005 16

R.Severn atCaerhowelBridge

SO1967098150

13 29/06/1993 29/12/2005 11

R.Severn at CilGwran BridgeAberbechan

SO1450093500

13 10/02/1988 21/12/2005 4

R.Severn atDolwen

SN9970085200

13 02/03/1988 22/12/2005 13

R.Severn atLlandrinio

SJ2980016900

7 10/02/1988 01/12/2005 9

R.Severn atLlanidloesFelindre Bridge

SN9440083901

10 02/03/1988 22/12/2005 5

R.Severn atMaginnisBridge

SJ2589011510

13 10/02/1988 09/12/2005

R.Severn at SJ432001530 7 18/02/1988 12/12/2005 9


Site NGR Typology Start date End date GapsMontfordBridge

0

R.Severn FootBridge BackLane CPNTON

SO1052091640

13 07/07/1988 09/12/2005 4

River Severnat Holt FleetMeadows, HoltFleet

SO8245063350

7 04/01/1988 12/12/2005 9

R Severn(Lower) HawBridge

SO8455027850

8 04/01/1988 08/12/2005 17

R Severn(Upper)Kempsey (Mid)

SO8465049500

8 09/07/1989 05/12/2005 24

R Severn(Upper)Tewkesbury

SO8887033720

8 12/01/1988 05/12/2005 16

R Severn –Upton onSevern

SO8516040750

8 04/01/1988 05/12/2005 14

R Severn –Caersws

SO0320091700

13 10/02/1988 21/12/2005 10

R Severn –rear of oildepot Bath RdWorcester

SO8510052320

7 20/06/1990 12/12/2005 26

R Severn – theIronbridge atIronbridge

SJ6725003400

7 02/08/1993 08/12/2005 12

R Severn –WorcesterBridge

SO8465054750

7 19/01/1988 12/12/2005 12

R Severn(Lower)Ashleworth

SO8190025060

8 15/01/1988 08/12/2005 22

R.Strine atCrudgington

SJ6300017800

1 25/02/1988 07/12/2005 13

Rea Brook atHorse Bridge

SJ3710005900

1 09/02/1988 15/12/2005 22

River Erewashat Shipley Gate

SK4633745440

2 04/12/1987 08/12/2005 12

River Erewashupstream ofMilnhay STW

SK4555146587

2 04/12/1987 08/12/2005 14

River Camladat Gaer Bridge

SO2140099900

4 10/02/1988 29/12/2005 45

R.Camlad atChirbury

SO2710098300

4 10/02/1988 29/12/2005 51

Non-tidal RiverTrent –Tittensor

SJ8750037700

5 22/02/1988 21/12/2005 4


Site NGR Typology Start date End date GapsRiver Idle(Maun) – atBawtry

SK6559092680

5 08/12/1987 16/12/2005 11

Non-tidal RiverTrent atGunthorpe

SK6821043757

8 31/12/1987 21/12/2005 1

River Soar atRed Hill Lock

SK4920030200

8 09/02/1988 24/11/2005 9

Afon Clywedog– new gaugingweir atClywedog

SN9130086800

10 02/03/1988 22/12/2005 10

R.Severn atLlanidloesFelindre Bridge

SN9440083901

10 02/03/1988 22/12/2005 5

River Wye atAshwood ParkBuxton

SK0639673544

11 11/03/1988 19/12/2005 17

R.Morda at theA483 Bridge

SJ2880028100

11 17/02/1988 09/12/2005 36

River Derwent– intake toLittle EatonWTW

SK3593640770

13 01/03/1988 28/12/2005 26

River Churnet– CheddletonStation

SJ9820052100

13 03/03/1988 17/11/2005 7

River Wye atRowsley

SK2570165684

14 11/03/1988 29/12/2005 21

River DoveMayfield

SK1580045800

14 03/03/1988 30/11/2005 16

River Dove,Monk's Bridge

SK2680027000

17 02/03/1988 23/11/2005 21

River Derwentat Wilne

SK4520231459

17 25/02/1988 06/12/2005 18

Marton Drainat A156 Bridgeat BramptonGrange

SK8416080980

40 15/12/1987 12/12/2005 46

Dimore BrookElmore

SO7928014810

40 22/01/1988 09/12/2005 53

Daily dataSevernSaxon's Lode

SO8633039050

8 01/01/1975 31/10/2006 332

Severn WelshBridge

SJ4888012730

7 01/01/1989 31/10/2006 3379

Teme atBransford

SO8038053240

8 01/01/1976 31/10/2006 2001

Clywedog atBryntail

SN9136086780

10 07/09/2000 31/10/2006 202

Avon atEvesham

SP0401043760

8 01/01/1978 31/10/2006 1344


Site NGR Typology Start date End date GapsVyrnwy atMeifod

SJ1563012920

13 01/01/1975 31/10/2006 1349


North East Region

Site NGR Typology Start date End date GapsMonthly dataNorth TyneatBarrasfordIntake

NY9200073200

2 30/08/1990 29/11/2005 47

North TyneatBellingham

NY8340083250

14 03/02/1981 08/12/2005 144

North TyneatChollerford

NY9180070500

2 03/04/1973 12/12/2005 57

North Tyneat Tarset

NY7820085600

14 03/04/1973 08/12/2005 39

North Tyneat Wark

NY8630077000

14 15/01/1974 08/12/2005 109

North Tyneu/s Kielder

NY6320092800

11 03/04/1973 28/11/2005 123

Tyne atBywell

NZ0520062000

2 03/04/1973 05/12/2005 56

Tyne atHexham

NY9410064600

2 03/04/1973 05/12/2005 60

Tyne atOvingham

NZ0840063400

2 13/03/1989 05/12/2005 34

Tyne atOvinghamIntake

NZ0968064240

2 29/08/1990 24/05/2005 81

Tyne atWylamBridge

NZ1190064600

2 13/03/1974 05/12/2005 43

Coquet atWarkworthDam

NU2370106065

1 05/04/1973 05/12/2005 40

Oak Beckat A61 roadbridge

SE2920057600

1 14/05/1974 01/12/2005 60

River DoeLea atRenishaw

SK4430077000

2 28/05/1974 17/11/2005 36

River Doveat Darfield(LowValley)

SE4070003800

2 01/04/1974 02/12/2005 76

Blyth atBedlingtonBridge

NZ2660081400

4 05/04/1973 05/12/2005 30

WansbeckatSheepwashDam

NZ2570085700

4 05/04/1973 29/11/2005 41

River Hull TA079844988 5 01/04/1974 24/11/2005 23


Site NGR Typology Start date End date GapsatHempholmeLock

5

Dearne atPasturesBridge

SE4980000800

5 01/04/1974 28/11/2005 25

River Ouseat NetherPoppleton(Skelton)

SE5580055100

8 03/04/1974 24/11/2005 30

River Aireat Beal

SE5328625553

8 30/06/1972 08/12/2005 43

RiverHolme atQueens Mill

SE1419415742

10 04/04/1974 01/12/2005 34

Little Don atDeepcar

SK2890098100

10 29/11/1974 08/11/2005 68

River Donat Deepcar

SK2920098100

11 05/04/1974 08/11/2005 54

River Donat OxspringBridge

SE2730002100

11 29/11/1974 18/11/2005 71

River DibbatHartlingtonBridge

SE0400060900

12 03/04/1974 29/11/2005 52

Lewisburnu/s Kielder

NY6365089650

12 03/04/1973 28/11/2005 126

RiverWharfeaboveTadcasterWeir

SE4850043700

13 03/04/1974 18/11/2005 18

RiverWharfe atBoltonBridge

SE0720052800

13 03/04/1974 06/12/2005 39

RiverCalder atMethleyBridge

SE4096825810

14 04/04/1974 30/11/2005 28

River Donat BSCRotherhamGate 14

SK4210092200

14 05/04/1974 05/12/2005 47

River Ouseat Cawood

SE5740037800

17 03/04/1974 05/12/2005 60

Tees atLowWorsall

NZ3910010200

17 26/04/1973 02/12/2005 64

Daily dataTyne atUgly Dub

NY7130087500

14 28/04/1993 22/11/2006 676


Site NGR Typology Start date End date GapsTyne atBywell

NZ3800061700

2 17/03/1993 22/11/2006 601

Tyne atSwingBridge

NZ2522863717

0 09/06/1995 10/10/2006 405

Ouse atCawoodBridge

SE5740037800

17 06/07/1992 02/10/2006 514

Humber atBlacktoftJetty

SE8430024200

0 10/09/1991 02/10/2006 339

Humber atCorporationPier

TA1000028200

5 19/12/1991 02/10/2006 650


North West Region

Site NGR Typology Start date End date GapsMonthly dataRiver Ribble atCleatop Barns

SD8077661390

14 03/05/1971 13/12/2005 64

River Ribble atCow Bridge

SD8267156968

14 18/01/1993 13/12/2005 18

River Ribble atEddisfordBridge

SD7265841441

14 05/12/1985 07/12/2005 110

River Ribble atHorton inRibblesdale

SD8069372707

11 14/01/1975 15/12/2005 155

River Ribble atMitton Bridge

SD7156038724

14 30/04/1971 16/12/2005 10

River Ribble atMitton WoodPTCRiverCalder

SD7103837400

14 08/06/1976 02/12/2005 47

River Ribble atPaythorn Bridge

SD8313051292

14 14/01/1975 13/12/2005 92

River Ribble atRibchesterBridge

SD6619435600

17 14/01/1975 16/11/2005 43

River Ribble atSamlesburyPGS

SD5888830433

17 30/04/1971 15/12/2005 11

River Ribble atSawley Bridge

SD7749146624

14 14/01/1975 06/12/2005 37

River Ribble atSettle Weir

SD8178764221

14 14/01/1975 15/12/2005 42

River Roe atGaitsgill

NY3879446590

1 28/09/1976 28/11/2005 98

River Ive at LowBraithwaiteBridge

NY4280342185

1 28/01/1981 28/11/2005 49

River Irk at RedBank aboveScotland Weir

SJ8419999171

2 23/04/1974 01/11/2005 16

River Yarrow atFishery BridgeCroston

SD4842618566

2 26/04/1972 12/12/2005 37

River Wyre atGubberfordBridge Scorton

SD4952247399

4 03/12/1974 05/12/2005 68

River Darwen atRoach Bridge

SD5957428820

4 02/06/1975 08/12/2005 97

River Irwell atfoot bridge atSalfordUniversity

SJ8225899020

5 01/10/1974 29/12/2005 5

River Alt above SD29211050 5 28/08/1974 16/12/2005 16


Site NGR Typology Start date End date GapsAltmouthPumpingStation

91

River Merseyabove HowleyWeir

SJ6159787999

8 26/09/1974 15/12/2005 1

River Weaver atFrodsham RoadBridge

SJ5301778474

8 18/09/1974 12/12/2005 4

River Esk atCropple HowGaugingStations

SD1309897770

10 21/06/1980 09/12/2005 56

River Ogdenaboveconfluence withRiver Irwell

SD7918720273

10 06/09/1960 08/12/2005 189

River Irwell atHolme BridgeTownsend Fold

SD8010521953

11 06/01/1960 24/08/2005 133

River Irwell PTCCowpe Brook

SD8362421686

11 06/01/1960 08/12/2005 140

Chew Brookaboveconfluence withRiver Tame

SD9957404191

12 07/01/1975 06/12/2005 61

River Etherowbelow BottomsReservoir

SK0205496961

12 12/01/1976 09/12/2005 87

River Irwellabove WarthWeir

SD7960409043

13 09/04/1974 08/12/2005 12

River Leven atLow WoodBridgeHaverthwaite

SD3449883600

13 24/02/1960 06/12/2005 138

River Calder atWhalley

SD7292736058

14 30/04/1971 15/12/2005 7

River Ribble atMitton Bridge

SD7156038724

14 30/04/1971 16/12/2005 10

River Etherowat railwayviaduct atBroadbottom

SJ9965493750

15 12/01/1976 09/12/2005 93

River Etherowbelowconfluence withGlossop Brook

SK0042594763

15 12/01/1976 09/12/2005 185

River Lune atDenny Bridge

SD5036464692

16 05/05/1971 14/12/2005 108

River Lune atCrook of LuneCaton

SD5219264600

16 02/04/1980 01/12/2005 146


Site NGR Typology Start date End date GapsRiver Ribble atSamlesburyPGS

SD5888830433

17 30/04/1971 15/12/2005 11

River Petteril atStonyholme

NY4114656439

17 12/01/1976 02/12/2005 52

River Weaver atSandfordBridge

SJ6197047057

28 10/08/1976 13/12/2005 90

Rookery Brookaboveconfluence withRiver Weaver

SJ6574855729

28 23/03/1977 13/12/2005 178


Southern Region

Site NGR Typology Start date End date GapsMonthly dataRiver Test atBridge StreetOverton

SU5136049795

5 22/01/1979 10/12/2005 32

River Test atEast AstonCommon

SU4434344882

5 30/06/1980 10/12/2005 77

River Test atGreatbridge

SU3526622884

5 03/07/1978 14/12/2005 8

River Test atLongbridge

SU3549917847

8 10/07/1978 14/12/2005 32

River Test atMayfly Inn

SU3817338974

5 22/01/1979 10/12/2005 48

River Test atMiddlebridgeRomsey

SU3492820675

5 14/07/1988 14/12/2005 14

River Test atPolhampton

SU5237550493

5 22/01/1979 10/12/2005 56

River Test atTestwood

SU3529415330

8 26/01/1979 09/12/2005 25

River Test atWherwell

SU3894540131

5 19/07/1978 10/12/2005 10

River TestLongstock atLeckford

SU3613436889

5 19/07/1978 10/12/2005 27

River TestupstreamAndover STW

SU3819539216

5 15/04/1997 10/12/2005 15

River Testupstream ofMeadow FishFarm

SU3303025781

5 25/01/1979 14/12/2005 39

River Testupstream ofTest ValleyTrout Farm

SU3503222681

5 24/01/1979 14/12/2005 26

River TestupstreamRomsey TroutFarm

SU3485021577

5 25/01/1979 14/12/2005 37

Town Mill,Whitchurch,River Test

SU4668048070

5 11/03/1981 10/12/2005 67

Wallers HavenBorehamBridge

TQ6761012000

1 06/01/1976 12/12/2005 18

Abstractionpoint onOuseby MSWCoy at Ardingly

TQ3320028320

1 05/01/1977 21/12/2005 25


Site NGR Typology Start date End date GapsRiver Arun atfootbridgedownstream ofHorshamBypass (A24)

TQ1505629987

2 10/08/1977 16/12/2005 79

River RotherDurford Bridge

SU7825023300

2 27/01/1976 01/12/2005 20

River Uck atIsfield Mill

TQ4480018030

4 15/01/1976 28/11/2005 31

RiverLymington atBoldre Bridge

SZ3199098441

4 03/04/1979 01/12/2005 19

River Arun atPallinghamManor

TQ0440022200

5 07/01/1976 16/12/2005 19

RiverCuckmereShermanBridge

TQ5320005050

5 07/01/1976 30/11/2005 10

RiverBlackwater atNutsey Bridge

SU3513015240

8 10/07/1978 12/12/2005 12

River Test atTestwood

SU3529415330

8 26/01/1979 09/12/2005 25

Broad RifeFerry Sluice,PaghamHarbour

SZ8563096280

37 08/01/1976 15/12/2005 32

Botley Streamat Broadoak

SU5062513053

37 08/01/1979 06/12/2005 64

ChichesterCanal BypassBridge – A27

SU8591003710

40 09/02/1977 14/12/2005 38

ChichesterCanal belowBirdham Weir

SU8376001070

40 18/05/1976 07/12/2005 50


South West Region

Site NGR Typology

Start date End date Gaps

Monthly dataRiver Tamar atBoyton Bridge belowBoyton Stw

SX3282592257

4 02/07/1974

15/12/2005

39

River Tamar atBuses Bridge

SS2808013380

1 05/01/1976

14/12/2005

90

River Tamar atCrowford Bridge

SX2872099425

1 05/01/1976

15/12/2005

82

River Tamar atfootbridge belowLower Tamar Lake

SS2956010700

1 21/05/1985

14/12/2005

20

River Tamar atGreystone Bridge

SX3683880363

4 05/01/1976

15/12/2005

66


SX4349372436

4 03/04/1974

15/12/2005

14

River Tamar atGunnislake GaugingStation

SX4265072500

4 12/05/1995

15/12/2005

10

River Tamar atHorsebridge

SX4000174889

4 05/01/1976

15/12/2005

69

River Tamar atLower Tamar LakeSurface

SS2960010800

1 29/08/1991

14/12/2005

13

River Tamar atNetherbridge

SX3487886703

4 05/01/1976

15/12/2005

78

River Tamar atPolson Bridge BelowSt Leonard's STW

SX3558484944

4 05/01/1976

15/12/2005

76

River Tamar atTamarstone Bridge

SS2832805503

1 05/01/1976

15/12/2005

79

River Tamar atTamerton Bridgebelow NorthTamerton STW

SX3182297405

1 05/01/1976

15/12/2005

78

River Tamar atUpper Tamar LakeDam surface

SS2880011800

1 29/08/1991

14/12/2005

18

River Tamar belowconfluence with RiverDeer

SX3191897257

4 23/01/1990

15/12/2005

17

River Tamarupstream LowerTamar Lake

SS2930011400

1 24/02/1992

14/12/2005

50

Carnon River atDevoran Bridgebelow Carnon DownsSTW

SW7908739436

1 01/04/1974

29/11/2005

16

River Wolf at RexonBr. belowBroadwoodwidger

SX4133088850

1 20/04/1976

02/12/2005

59


Site NGR Typology


STWDolphin Bridge d/sFrome SW

ST7724649589

2 11/03/1969

30/11/2005

119

River Brit at WatfordBridge Pymore

SY4722694952

2 17/01/1977

08/12/2005

42


SX4349372436

4 03/04/1974

15/12/2005

17

River Lyd at LiftonBridge

SX3891184838

4 03/04/1974

02/12/2005

19

Great SomerfordBridge u/s gaugingstation

ST9651183193

5 06/01/1966

15/12/2005

104

River Axe at WhitfordBridge

SY2622595420

5 22/04/1974

01/12/2005

41

River Exe at TrewsWeir Exeter

SX9254691506

7 08/05/1974

17/11/2005

55

Alphin Brook atCountess WearBridge

SX9398389386

7 29/04/1974

17/11/2005

152

Avon Limpley Stoke ST7823661244

8 12/08/1975

17/11/2005

63

Avon Keynsham ST6616369000

8 28/08/1968

21/11/2005

49

River Erme atSequer's Bridge

SX6321051880

10 15/07/1974

03/12/2005

107

River Walkham atGrenofen Bridge

SX4900770972

10 03/04/1974

28/11/2005

40

River Culm atBridgehouse BridgeClayhidon

ST1599214087

11 12/08/1974

07/12/2005

82

River Culm atCulmstock AboveCulmstock STW

ST1011513773

11 02/12/1974

07/12/2005

81

River Tavy atDenham Bridge

SX4769067760

13 25/06/1973

28/11/2005

19

River Plym at PlymBridge

SX5236658732

13 03/04/1974

01/12/2005

14


Thames RegionSite NGR Typology Start date End date GapsMonthly dataThamesAbove NswcIntake,Egham

TQ0225071820

8 05/01/1972 01/12/2005 46

Thames atAbingdonWeir

SU5067697128

8 04/01/1972 21/12/2005 50

Thames atBoveney Weir

SU9440077700

8 12/04/1976 15/12/2005 42


SU7213574053

8 05/01/1972 09/12/2005 13

Thames atDays Lock

SU5676093498

8 04/01/1972 25/11/2005 34

Thames atDonningtonBridge,Oxford

SP5245904368

8 06/06/1989 21/12/2005 26

Thames atEysey

SU1128794056

5 03/05/1973 19/12/2005 40

Thames atHenley Bridge

SU7631982813

8 11/01/1972 09/12/2005 35

Thames atSonning Weir

SU7533475895

8 05/01/1972 09/12/2005 69

Thames atwater intake,Buscot

SU2290098100

8 05/01/1972 19/12/2005 38

Thames atTeddingtonWeir

TQ1702071370

0 05/01/1972 02/12/2005 16

BoveneyDitch aboveThames

SU9486078120

1 20/01/1972 29/11/2005 66

Blackwater atLynchfordBridge, AshVale

SU8852053770

1 09/02/1972 25/11/2005 33

HogsmillaboveThames

TQ1785069100

2 27/01/1972 02/12/2005 41

Cherwell atRoadbridge,Twyford

SP4869137222

2 12/01/1972 22/11/2005 37

Wey atCartbridge,Send

TQ0152055920

4 05/02/1975 02/12/2005 33

Wey atNewark Lane,Pyrford

TQ0390057370

4 05/02/1975 02/12/2005 35

Lee at TL299000990 5 22/05/1974 14/12/2005 33


Site NGR Typology Start date End date GapsWaterhall 0Colne atGaugingStation,Denham

TQ0520086300

5 25/01/1972 06/12/2005 19


SU7213574053

8 05/01/1972 09/12/2005 13

ThamesaboveNSWCIntake,Egham

TQ0225071820

8 05/01/1972 01/12/2005 46

Eye at LowerSlaughter Mill

SP1640022600

11 05/01/1976 28/11/2005 93

Churn atNorth Cerney

SP0200007800

11 17/03/1977 01/12/2005 143

Beam atHaveringSluice

TQ4991981556

40 05/04/1978 01/12/2005 74

Beam at A13bridge

TQ5030083100

40 05/04/1978 01/12/2005 74

Daily dataPymmesBrook Angel

TQ3398592538

2 01/02/1997 30/06/2006 1218

Thames Bray SU9147878877

8 01/02/1997 30/06/2006 172

ThamesRomney

SU9680077500

8 03/06/1986 23/03/2006 1445

WeyWeybridge

TQ0680064900

4 03/06/1986 05/06/2006 732

KennetTheale

SU6480070800

8 03/06/1986 30/06/2006 886

Lee Waterhall TL2980009700

5 03/06/1986 14/02/2006 1322

ThamesSunbury

TQ1040068000

8 12/08/1989 21/04/2006 535

Lee KingsWeir

TL3730005200

8 17/03/1987 30/06/2006 824

ThamesCleave

SU6010081800

8 03/06/1986 01/07/2005 945

ThamesTeddington

TQ1700071350

0 16/06/1986 30/06/2006 1637

ThamesHannington

SU1750096000

5 23/06/1986 23/04/2004 852

ThamesPenton Hook

TQ0430069300

8 25/07/1989 30/06/2006 678

ThamesMolsey

TQ1490068900

8 21/07/1989 31/05/2006 683

ThamesTaplow

SU9062883221

8 10/01/1997 31/03/2005 231

LoddonWargrave

SU7770077300

5 01/01/1997 05/02/2006 636



Wales Region

Site NGR Typology


Monthly dataRiver Dee at B5437near Corwen

SJ0820043900

13 01/05/1992

29/11/2005

16

River Dee at ChesterWeir

SJ4084065850

17 06/04/1981

25/05/2005

201

River Dee atFarndon Bridge

SJ4117054370

17 01/05/1979

02/12/2005

32

River Dee atGlyndyfrdwy

SJ1510043050

13 01/05/1979

29/11/2005

72


SJ4180060100

17 09/04/1974

29/11/2005

25

River Dee atLlandderfel Bridge

SH9820036610

13 09/04/1974

01/12/2005

26

River Dee atNewbridge

SJ2873041800

13 04/04/1979

29/11/2005

23

River Dee at OldBangor Bridge

SJ3880045420

17 28/04/1992

21/11/2005

8

River Dee at OvertonBridge

SJ3542042700

17 21/05/1992

21/11/2005

9

River Dee at PontMwnwgl y Llyn

SH9295935134

13 12/09/1979

01/12/2005

76

River Dee atQueensparkSuspension Bridge

SJ4103066010

17 30/04/1992

12/12/2005

13

River Dee,at Chestersoutherly by-pass

SJ4142163363

17 27/04/1980

22/12/2005

87

River Llan atGowerton

SS5890096800

1 03/05/1977

09/12/2005

78

Pontardulais RoadBridge

SN5880003800

1 06/05/1975

25/11/2005

82

River Gwenfro u/s ofRiver Clywedog

SJ3472049140

2 17/04/1979

06/12/2005

55

River Clywedog u/sof River Gwenfro

SJ3470049110

2 08/06/1979

06/12/2005

61

R Rhymney atLlanrumney

ST2140980755

4 27/09/1974

13/12/2005

79

W CleddauPrendergastGauging Station

SM9540017700

4 02/06/1976

29/11/2005

39

Loughor above YnysLlwchwr GaugingStation

SN6146108764

5 28/03/1974

06/12/2005

42

R Ely at St Fagans(u/s St FagansGauging Station)

ST1194076960

5 27/09/1974

12/12/2005

20

R Afan at DockIntake Weir

SS7606089740

10 18/04/1977

21/11/2005

77

River Seiont, PontPen-y-Llyn, Llanberis

SH5593062330

10 04/06/1979

07/12/2005

103


Site NGR Typology


Afon Lwyd,Llanyravon

ST3018494644

11 16/02/1977

17/11/2005

58

River TaweYstradgynlais RoadBridge,Ystradgynlais,Powys

SN7860010100

11 19/04/1977

23/11/2005

82

River Tawe atMorriston RoadBridge

SS6740097900

13 15/03/1974

06/12/2005

51

R Ogmore atMerthyrmawr,Dipping Bridge

SS8910078400

13 27/09/1974

05/12/2005

45

River Alyn at IthelsBridge

SJ3902056230

14 09/04/1974

14/12/2005

46

R Neath d/sAberdulais GaugingStation

SS7715098910

14 27/09/1974

05/12/2005

77

Towy Nantgaredig,nr Carmarthen,Dyfed

SN4910020400

16 22/03/1974

02/12/2005

86

Gwili at AbergwiliRoad Bridge, nrCarmarthen, Dyfed

SN4335021040

16 21/04/1977

08/12/2005

85


SJ4180060100

17 09/04/1974

29/11/2005

29

R Wye at CarrotsPool, HamptonBishop

SO5497038190

17 02/11/1965

12/12/2005

75

Daily dataTaff Blackweir ST170607805

313 14/12/199

301/11/200

61003

Wye Belmont SO4850038799

17 13/01/1997

09/12/2006

190

Wye Redbrook SO5276911077

17 01/01/1996

09/12/2006

166

Tywi Capel Dywi SN4851920582

16 01/09/1997

04/01/2007

476

Tywi Manoravon SN6574123987

13 01/09/1997

03/01/2007

463

Tywi Dolau Hirion SN7618936242

13 01/09/1997

03/01/2007

445

Tywi Ystradffin SN7855947241

10 01/09/1997

04/01/2007

879

Dee Summers Jetty SJ2904670696

0 08/11/1995

15/01/2007

234

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